#and started writing the code for stats analysis

[falciesystemessays]

Alright, let's make this quick. You're playing a dress-up game, maybe Style Savvy, maybe Love Nikki, because you want to express yourself creatively. The game gives you some explicit goals, it is a game after all. Maybe it's to dress up in a certain theme, maybe it's to max out certain stats, but the goal is to use incentives to make you try different outfits. Fair enough, right?

Here's the problem though: Players will naturally gravitate towards the solution with the most reward. There's a common joke in RPG spaces about wearing ugly armor for better stats, but it is so much worse in a game where dressing nicely is the primary appeal. Love Nikki is especially nasty in this regard, giving you an exact score on how fashionable it thinks you are.

This is what game designer Alex Jaffe calls the "Quantified Creativity Problem," and it is one of many Cursed Problems in Game Design. As he lays out, a cursed problem is one that is unsolvable, because it comes out of a contradiction of two core promises. In this case, you come into a game like Style Savvy (but this also applies to other games like The Sims) for intrinsic goals of creativity and expression. But these extrinsic goals inherently detract from the intrinsic joy of creation.

If you want to deal with a cursed problem, you have to make some kind of sacrifice to one of the promises.

You could

Embrace the bastard behavior and say "this isn't about creativity, you're dressing up for explicit goals." This is what the Hitman reboots do, for instance. You're not dressing up for aesthetics, you're dressing up for stealth.

Incentivize creativity like the games I've described try to do. This does certainly give a variety of ideas for nice outfits. However, as I've laid out, this does still detract from the intrinsic motivators.

Simply make it impossible to minmax, which here would manifest as clothing options having no mechanical attributes at all. This is what Picrews and doll-makers are, and while they're fun in their own way, I personally feel a sense of aimlessness and overchoice with a lot of these.

Make the extrinsic motivators less intense, although still there. This is what Artificial Fashionista does, which is my favorite of all of these and the reason I'm writing this essay.

So, this game is very nice, for a variety of reasons. The game is free, with regular DLC rather than scummy microtransactions. Its writing is genuinely well-executed in making every character delightfully annoying. But more than that, it's the first fashion game I've played that gives me direction without making me feel pressured.

Simply put, the game still has Nikki-style stat requirements, for example the starting Office Lady mission requires 4 points in Cool and 6 points in Formal. However, you are shown every single clothing item's exact stats in advance, and the game will straight-up tell you when the outfit you've made meets the requirement, as well as its equivalent of an S-Rank.

And the game has no actual scoring system above that rank, so you can dress in any way as long as it meets the threshold. Which means that this

and this

are both equally valid in the game's terms. I call that second look "violating the dress code but no one seems to mind," by the way.

What this all amounts to is a dress-up game that gives you just enough direction to come up with unique outfits, while giving you the room to be creative to your own liking. Sure, you probably won't make the "expected" outfit, but that's part of the fun of it! Artificial Fashionista confidently cuts through the Quantified Creativity problem by making the game easier than most other games of its type, and honestly? I appreciate that.

I'm talking about fashion games like this because I think it's a sorely needed discussion in our discourse about game design. Like, most of the Game Analysis I've seen on social media and YouTube tends to be very focused on challenge. Level design, systems design, and pacing tend to be made with idea of "game as challenge to overcome" as the primary appeal. But there are many different appeals a game can have, and expression is a big one. So why don't I see dress-up games brought up more often in these discussions?

I say, knowing the answer.

(Also, check out "Why Fashion in (Most) Games Sucks, and Why You Should Care", a GDC talk by Victoria Tran that I like a lot!)

[kanguin]

Hi, idk who's going to see this post or whatnot, but I had a lot of thoughts on a post I reblogged about AI that started to veer off the specific topic of the post, so I wanted to make my own.

Some background on me: I studied Psychology and Computer Science in college several years ago, with an interdisciplinary minor called Cognitive Science that joined the two with philosophy, linguistics, and multiple other fields. The core concept was to study human thinking and learning and its similarities to computer logic, and thus the courses I took touched frequently on learning algorithms, or "AI". This was of course before it became the successor to bitcoin as the next energy hungry grift, to be clear. Since then I've kept up on the topic, and coincidentally, my partner has gone into freelance data model training and correction. So while I'm not an expert, I have a LOT of thoughts on the current issue of AI.

I'll start off by saying that AI isn't a brand new technology, it, more properly known as learning algorithms, has been around in the linguistics, stats, biotech, and computer science worlds for over a decade or two. However, pre-ChatGPT learning algorithms were ground-up designed tools specialized for individual purposes, trained on a very specific data set, to make it as accurate to one thing as possible. Some time ago, data scientists found out that if you have a large enough data set on one specific kind of information, you can get a learning algorithm to become REALLY good at that one thing by giving it lots of feedback on right vs wrong answers. Right and wrong answers are nearly binary, which is exactly how computers are coded, so by implementing the psychological method of operant conditioning, reward and punishment, you can teach a program how to identify and replicate things with incredible accuracy. That's what makes it a good tool.

And a good tool it was and still is. Reverse image search? Learning algorithm based. Complex relationship analysis between words used in the study of language? Often uses learning algorithms to model relationships. Simulations of extinct animal movements and behaviors? Learning algorithms trained on anatomy and physics. So many features of modern technology and science either implement learning algorithms directly into the function or utilize information obtained with the help of complex computer algorithms.

But a tool in the hand of a craftsman can be a weapon in the hand of a murderer. Facial recognition software, drone targeting systems, multiple features of advanced surveillance tech in the world are learning algorithm trained. And even outside of authoritarian violence, learning algorithms in the hands of get-rich-quick minded Silicon Valley tech bro business majors can be used extremely unethically. All AI art programs that exist right now are trained from illegally sourced art scraped from the web, and ChatGPT (and similar derived models) is trained on millions of unconsenting authors' works, be they professional, academic, or personal writing. To people in countries targeted by the US War Machine and artists the world over, these unethical uses of this technology are a major threat.

Further, it's well known now that AI art and especially ChatGPT are MAJOR power-hogs. This, however, is not inherent to learning algorithms / AI, but is rather a product of the size, runtime, and inefficiency of these models. While I don't know much about the efficiency issues of AI "art" programs, as I haven't used any since the days of "imaginary horses" trended and the software was contained to a university server room with a limited training set, I do know that ChatGPT is internally bloated to all hell. Remember what I said about specialization earlier? ChatGPT throws that out the window. Because they want to market ChatGPT as being able to do anything, the people running the model just cram it with as much as they can get their hands on, and yes, much of that is just scraped from the web without the knowledge or consent of those who have published it. So rather than being really good at one thing, the owners of ChatGPT want it to be infinitely good, infinitely knowledgeable, and infinitely running. So the algorithm is never shut off, it's constantly taking inputs and processing outputs with a neural network of unnecessary size.

Now this part is probably going to be controversial, but I genuinely do not care if you use ChatGPT, in specific use cases. I'll get to why in a moment, but first let me clarify what use cases. It is never ethical to use ChatGPT to write papers or published fiction (be it for profit or not); this is why I also fullstop oppose the use of publicly available gen AI in making "art". I say publicly available because, going back to my statement on specific models made for single project use, lighting, shading, and special effects in many 3D animated productions use specially trained learning algorithms to achieve the complex results seen in the finished production. Famously, the Spider-verse films use a specially trained in-house AI to replicate the exact look of comic book shading, using ethically sources examples to build a training set from the ground up, the unfortunately-now-old-fashioned way. The issue with gen AI in written and visual art is that the publicly available, always online algorithms are unethically designed and unethically run, because the decision makers behind them are not restricted enough by laws in place.

So that actually leads into why I don't give a shit if you use ChatGPT if you're not using it as a plagiarism machine. Fact of the matter is, there is no way ChatGPT is going to crumble until legislation comes into effect that illegalizes and cracks down on its practices. The public, free userbase worldwide is such a drop in the bucket of its serverload compared to the real way ChatGPT stays afloat: licensing its models to businesses with monthly subscriptions. I mean this sincerely, based on what little I can find about ChatGPT's corporate subscription model, THAT is the actual lifeline keeping it running the way it is. Individual visitor traffic worldwide could suddenly stop overnight and wouldn't affect ChatGPT's bottom line. So I don't care if you, I, or anyone else uses the website because until the US or EU governments act to explicitly ban ChatGPT and other gen AI business' shady practices, they are all only going to continue to stick around profit from big business contracts. So long as you do not give them money or sing their praises, you aren't doing any actual harm.

If you do insist on using ChatGPT after everything I've said, here's some advice I've gathered from testing the algorithm to avoid misinformation:

If you feel you must use it as a sounding board for figuring out personal mental or physical health problems like I've seen some people doing when they can't afford actual help, do not approach it conversationally in the first person. Speak in the third person as if you are talking about someone else entirely, and exclusively note factual information on observations, symptoms, and diagnoses. This is because where ChatGPT draws its information from depends on the style of writing provided. If you try to be as dry and clinical as possible, and request links to studies, you should get dry and clinical information in return. This approach also serves to divorce yourself mentally from the information discussed, making it less likely you'll latch onto anything. Speaking casually will likely target unprofessional sources.

Do not ask for citations, ask for links to relevant articles. ChatGPT is capable of generating links to actual websites in its database, but if asked to provide citations, it will replicate the structure of academic citations, and will very likely hallucinate at least one piece of information. It also does not help that these citations also will often be for papers not publicly available and will not include links.

ChatGPT is at its core a language association and logical analysis software, so naturally its best purposes are for analyzing written works for tone, summarizing information, and providing examples of programming. It's partially coded in python, so examples of Python and Java code I've tested come out 100% accurate. Complex Google Sheets formulas however are often finicky, as it often struggles with proper nesting orders of formulas.

Expanding off of that, if you think of the software as an input-output machine, you will get best results. Problems that do not have clear input information or clear solutions, such as open ended questions, will often net inconsistent and errant results.

Commands are better than questions when it comes to asking it to do something. If you think of it like programming, then it will respond like programming most of the time.

Most of all, do not engage it as a person. It's not a person, it's just an algorithm that is trained to mimic speech and is coded to respond in courteous, subservient responses. The less you try and get social interaction out of ChatGPT, the less likely it will be to just make shit up because it sounds right.

Anyway, TL;DR:

AI is just a tool and nothing more at its core. It is not synonymous with its worse uses, and is not going to disappear. Its worst offenders will not fold or change until legislation cracks down on it, and we, the majority users of the internet, are not its primary consumer. Use of AI to substitute art (written and visual) with blended up art of others is abhorrent, but use of a freely available algorithm for personal analyticsl use is relatively harmless so long as you aren't paying them.

We need to urge legislators the world over to crack down on the methods these companies are using to obtain their training data, but at the same time people need to understand that this technology IS useful and both can and has been used for good. I urge people to understand that learning algorithms are not one and the same with theft just because the biggest ones available to the public have widely used theft to cut corners. So long as computers continue to exist, algorithmic problem-solving and generative algorithms are going to continue to exist as they are the logical conclusion of increasingly complex computer systems. Let's just make sure the future of the technology is not defined by the way things are now.

[characteroulette]

All the cool kids are doing it, so. I guess, year in review for me.

First off, I finished Game Kids! like, officially. Still so insane to me that my love letter to video games and Code: Lyoko is now complete. Wow. Their story is ended for now. I even finished my 2 year long comic project for them waow. (Although I did write a chapter I mused about having the series end on that explains what happened to Dante, if you were interested in seeing that. I didn't put it in the book in the end because each one starts and ends with the character's narration who is the main focus of that book.)

(also while I'm promo-ing my original stuff, go read my Moon Sickness series. I started it last year but wrote some good stuff for it this year too.)

Secondly, I participated in a big bang! Fun and scary stuff. Absolutely go look at everyone's work, it's all fantastic. I made an ukagaka for it! Fun times for sure.

Third, I wrote my explanation for Snufpollo! Hooray!! The RGB boys have been haunting me since last year, but @detective-piplup and I have done a good job just going buckwild over them this past year lmao. I have contributed best I can (with some highlights being unhinged Snufkin in Prosecutor Luke au, isat flavoured Snufkin in RPG au, and the saddest Snufkin fic I have written so far lmao) and I'm gonna write more next year, I'm sure XD

Speaking of, ao3 stats say I wrote 400k words this year! wow. didn't get around to updating FtSotM, unfortunately (an update is in the works it's just taking me a while to get through the culture fest augh), but I did update several other of my fics I am trying to finish (Crystal Scriptlocke and Laywright Werewolf being the key two). It was an insane start to the year because ISAT is still on my mind, Siffrin my buddy Siffrin....

Also shoutout to my Study on Prosecutors I wrote the first 3/4ths of in just two days. This year was for insane writing and also meta analysis for sure. XD

[sonadukane]

How to Become a Data Scientist in 2025 (Roadmap for Absolute Beginners)

Want to become a data scientist in 2025 but don’t know where to start? You’re not alone. With job roles, tech stacks, and buzzwords changing rapidly, it’s easy to feel lost.

But here’s the good news: you don’t need a PhD or years of coding experience to get started. You just need the right roadmap.

Let’s break down the beginner-friendly path to becoming a data scientist in 2025.

✈️ Step 1: Get Comfortable with Python

Python is the most beginner-friendly programming language in data science.

What to learn:

Variables, loops, functions

Libraries like NumPy, Pandas, and Matplotlib

Why: It’s the backbone of everything you’ll do in data analysis and machine learning.

🔢 Step 2: Learn Basic Math & Stats

You don’t need to be a math genius. But you do need to understand:

Descriptive statistics

Probability

Linear algebra basics

Hypothesis testing

These concepts help you interpret data and build reliable models.

📊 Step 3: Master Data Handling

You’ll spend 70% of your time cleaning and preparing data.

Skills to focus on:

Working with CSV/Excel files

Cleaning missing data

Data transformation with Pandas

Visualizing data with Seaborn/Matplotlib

This is the “real work” most data scientists do daily.

🧬 Step 4: Learn Machine Learning (ML)

Once you’re solid with data handling, dive into ML.

Start with:

Supervised learning (Linear Regression, Decision Trees, KNN)

Unsupervised learning (Clustering)

Model evaluation metrics (accuracy, recall, precision)

Toolkits: Scikit-learn, XGBoost

🚀 Step 5: Work on Real Projects

Projects are what make your resume pop.

Try solving:

Customer churn

Sales forecasting

Sentiment analysis

Fraud detection

Pro tip: Document everything on GitHub and write blogs about your process.

✏️ Step 6: Learn SQL and Databases

Data lives in databases. Knowing how to query it with SQL is a must-have skill.

Focus on:

SELECT, JOIN, GROUP BY

Creating and updating tables

Writing nested queries

🌍 Step 7: Understand the Business Side

Data science isn’t just tech. You need to translate insights into decisions.

Learn to:

Tell stories with data (data storytelling)

Build dashboards with tools like Power BI or Tableau

Align your analysis with business goals

🎥 Want a Structured Way to Learn All This?

Instead of guessing what to learn next, check out Intellipaat’s full Data Science course on YouTube. It covers Python, ML, real projects, and everything you need to build job-ready skills.

https://www.youtube.com/watch?v=rxNDw68XcE4

🔄 Final Thoughts

Becoming a data scientist in 2025 is 100% possible���— even for beginners. All you need is consistency, a good learning path, and a little curiosity.

Start simple. Build as you go. And let your projects speak louder than your resume.

Drop a comment if you’re starting your journey. And don’t forget to check out the free Intellipaat course to speed up your progress!

[loregoddess]

🤍🖤 for Triangle Strategy!

Okay before I get to the questions I wanna ramble a little bit bc like, discussing morality in fiction is weird, but really interesting, but also can be kind of messy so I'm gonna just lay out some thoughts I have about it bc *vaguely gestures at long history of writing research papers in college which rewired my brain a bit*.

Anyhow, morality in fiction is a weird thing to discuss bc everyone has their own sense of morality which is deeply subjective and heavily influenced by culture and time period and social stuff. Personally, I don't often find "is [character]'s actions morally good or morally bad (according to my moral code)?" to be as useful a question for critical analysis in fiction as a lot of fandom spaces currently seem to think it is. It's not never useful, but it's more reflective of the audience's experience rather than like, analyzing the narrative, and I find sometimes if I set aside my own moral feelings towards a Thing In Fiction and actually look at the narrative fabric, I find more interesting things to dissect.

So I think it's important to look at the morals presented in the story. Like, what defines a character's moral code and how does this affect the their actions and decisions in the story? Do these morals change for the character, and if so why? What are the morals presented in the fictional culture(s) of the story's world? How does this tie in w/ the themes of the overall story? And so on and so forth.

But also experiencing a story doesn't happen in a vacuum, so it's important to discuss our own thoughts and feelings on a work in relation to our own morals as well, just, remembering that a work of fiction's morals don't have to equate with our own morals to be interesting and worthy of analysis and discussion.

So, I'm approaching these questions as both a "how do the morals in the story work, and what does the characterization tell us?" and a "and how did my reaction/feelings towards this affect my perceptions of the character or story?".

Anyhow, now to the questions. (Under the cut bc *sighs* I am apparently an essayist at heart). Also I know Morality is a literal stat in the game, but for the sake of my sanity, we're not....we're not going to worry about that stat. Just character analysis this time around.

🤍: Which character is not as morally bad as everyone else seems to think?

Roland, probably. Don't get me wrong, I had the same "what the fuck?" knee-jerk reaction to his Ch17 proposal that many others did, but when I got around to seeing his Ch15 character arc like, Ch17 wasn't out of character for him per se, and it actually matches the plot beats for Benedict's and Frederica's arcs as well, and ties in with the overall themes of the narrative really poetically, if tragically.

Every single major conviction character (Benedict, Frederica, and Roland) start the game each with their own set of morals that they operate by, and those sets of morals go through a major paradigm shift in each of their Ch15s (and while Ch15 is where the characters break, it can be argued that their moral codes were already being strained and tested bc of the entire war). Every character, not just Roland, proposes an idea that goes against their core morals from the start of the game.

Benedict starts by caring deeply about Serenoa and House Wolffort, and he values Serenoa's happiness; Symon's death twists that care into obsession with preserving House Wolffort and usurping Regna's legacy, and Benedict loses all care for any of Serenoa's feelings or wishes. Frederica begins the game wanting to learn more about the Roselle, but also entirely unwilling to sacrifice anyone (she is very outspokenly opposed to handing Roland over to Aesfrost early in the game); when she learns the truth, the whole truth, about the Roselle's long oppression, she becomes entirely focused on saving only them, so much so that she's willing to forsake an entire continent to do so. And Roland begins the game with his bright-eyed, if naïve, sense of justice, his desire to protect everyone and especially those who can't protect themselves; and when he's confronted with all the ugly corruption rampant in his own backyard as a mold that's been festering for ages, it breaks his last bit of resolve, and he's willing to accept that a false peace built on the suffering of the few is acceptable if it means the many will have peace of any sort.

(Obviously, both Hyzant's "peace" and Aesfrost's "meritocracy" are flawed, and the narrative shows us those flaws early on, so the fact that Benedict turns to Aesfrost's style of government and Roland turns to Hyzant's in their routes shows how far they've each fallen from their own ideals and morals. It's an intentionally written tragic spiral for both characters).

The thing is that Roland's route is, I think to a Western audience at least, the most horrific, since it means damning an entire race of people who were already oppressed. Given the current social and political climate around race, that didn't sit well with a lot of Western players, myself included, and made Frederica's route seem the most palatable of the non-golden routes.

But the other two non-golden routes are written to be just as morally bankrupt as Roland's endroute in the context of the overall narrative beats and themes.

Benedict orchestrates the implementation of a meritocracy, which is fundamentally flawed in the sense that not just "anyone" can work their way to the top via their merits, since people going into this new era are still coming from places of privilege or lack. We know this to be true even in the fabric of the game narrative because of the differences shown narratively between Avlora and Rudolph's life stories. Both are Aesfrosti orphans, which is mostly a meritocracy, but Avlora had the fortune of being taken in by Svarog, a very high-ranking and well-off noble, and while she still had to work her ass off it's likely that being in Svarog's care allowed her to opportunity to become general at all (since she would have been cared for if she fell ill, probably had a place to safely sleep, access to food, etc). Meanwhile, Rudolph had no such savior, and turns to a life of crime to try and save his younger brother, which results in his brother's death after Rudolph's arrest. He never even had the chance to climb Aesfrost's hierarchy, as Avlora had, because his entire situation put him at a disadvantage from the start.

Likewise at the end of Benedict's route we see that the Roselle, despite being rescued, are still suffering terribly bc they don't get to start up in the new meritocracy with the privileges that say, Glenbrook's nobles have; nor do those who started off poor, nor does anyone else who ends up flocking to Roland's cause in Benedict's ending. Benedict's choice to savagely put House Wolffort in rule and his disregard for Serenoa's--or anyone's--feelings on the matter damns and forsakes just as many people as Roland's ending.

Frederica's route is the one I found to be most palatable to my own moral senses, as if feels more "just" because she is freeing an oppressed and abused people. But, from a narrative perspective, she's still abandoning her early-story moral code, and causing a great deal of suffering to a large group of people, since she also leaves an entire continent--three countries worth of people--to burn in the fires of a hellish civil war. One that will again, likely hit the least privileged people the hardest. Where Roland's route is "the few suffer so the majority may live in peace" and Benedict's is a "any with strength to grasp their future will flourish while the rest will fall", Frederica's route is a "all who were oppressed with find salvation, while all who stood by will perish, regardless of whether they had the knowledge or power to stop the oppression". To her, the needs of the few do outweigh the needs of the many, because those few have suffered far longer and far worse than the many, regardless of the fact that leaving many to suffer other types of horrors still isn't just.

So it's not necessarily that Roland's route is "more morally bad" or "less morally bad", or at least the narrative doesn't seem to treat it as such. All three routes are fundamentally immoral, but in different ways. All three of the characters are trying to answer a "trolley problem" but all three are standing on different tracks and seeing all the potential victims differently, and their personal motives are all focused on different outcomes, so they're all willing to pull a different lever. No matter what, vast amounts of people are going to suffer and die.

The narrative writing for Benedict, Frederica, and Roland makes it apparent that each character has their own moral code, and they follow it, and also that their moral code can and does change due to extreme circumstances. The in-game morals and moral shifts are really well-written in my opinion, my own moral code and feelings towards those characters' choices aside, so overall I feel like the writing is still solid, and that the writers' intention was that all the non-golden routes would be immoral in some form or another for the characters involved, and furthermore that each character's departure from their initial core morals is fundamentally a tragedy.

🖤: Which character is not as morally good as everyone else seems to think?

Uhh...well I guess I sorta answered this in my long ramble for the first question, since "Frederica still leaves a continent to burn and that's not really a moral thing to do" is understandably definitely not a take that a lot of people are warm to, so uh, yeah!

Again, this hits the "morality is weird to talk about in fiction" thing I was getting at earlier. Because all the characters arcs, from the main cast to side characters, support and underscore the themes of tragedy throughout the entire Triangle Strategy narrative. War is brutal, and the people with the least power will always suffer the most because of the actions of their leaders, and this is a lamentable, horrific tragedy. Poetic, excellent thematic narrative writing. My own morals still bias me to see Frederica in a kinder light, but I won't deny that her route is just as dark as the other two non-golden endings. But this is also a work of fiction where we can explore darker things safely, and I still think every character's writing is excellent, and I respect that the themes and characterizations are consistently written.

So eh, I dunno, make of all that what you will. Morality is a messy, difficult subject to discuss. I don't really think there's a truly right or wrong "answer" to looking at morality in fiction, but damn if it doesn't make me want to go and stare at a wall for a bit sometimes.

[theuniversitychallengereview]

Some Good Old Fashioned Number Crunching

Winningest

Imperial and Manchester are the two winningest institutions in University Challenge history.

Whenever I have used 'winningest' in the past I have always done so with an air of the tongue-in-cheek. With the assumption that it wasn't actually a real word, and that it was just something American sports commentators said. But it has just occurred to me that not everyone reading this will be consumers of American sports commentary, so to those people it may be coming across as bizarre at best, or just downright wrong.

However, in the manner of fleek, skibidi toilet and bae, it has entered the conventional and agreed upon lexicon. Language is constantly evolving, and as demonstrated by the wave of ever-cringier TikToks/adverts doing the rounds on Twitter this week, new terms are constantly being coined.

But back to Manchester and Imperial.

Let's Crunch Some Numbers

I have finally managed to do some data analysis. This is something I've been saying I was going to do for years, but I've never done it.

Until now.

I thought I'd need to write some proper code for it and (not knowing how to write proper code) have been put off.

What I was forgetting is that most of the time a Pivot table will do.

Pivot tables - the saviour of many a work-spreadsheet (and of my iTunes most played artists data, as I discussed in this month's Patreon post) - have come up clutch once again. (Coming up clutch is another American sports-ism, incidentally).

So I have crunched some numbers on these most winningest of teams, and can share some with you below.

Appearance Data

4-time winners Magdalen are the most appearingest (okay, this one isn't a real word) Oxbridge college with 1 more appearance than Trinity, Cambridge (themselves 3-time winners).

I initially had Durham 4th, but at the last minute I spotted an oversight - 11 of their appearances had been logged as "Uni of Durham" rather than "Durham Uni". It is very possible that there are more errors like that in the data, so if you spot any mistakes please let me know.

But how many points have each of these institutions scored, I hear you ask. I hear you clamouring for that information, actually - and here it is.

So far we have done some counting (to get the number of appearances), and some adding (to get the sum of the points), but we haven't done any real number crunching, which is what I promised.

I have removed institutions with fewer than 10 episodes, because thats the kind of thing you do when you are crunching numbers. I will also note that although some of the teams look like they have the same points per game, when you go to multiple decimal places the order is correct. I could have made this more obvious by adding the decimal places to the table, but I think that would have made it a bit busy.

I don't want to waste all my stats ammo on one post, so let's move onto the episode - could Imperial start closing the appearance gap on Manchester?

If you want to watch the episode beforereading the rest of the post you can do so here.

Here's your first starter for ten.

Sutherland is first out of the gate for Manchester, but unfortunately her guess of moth is wrong. I had guessed butterfly, so was thinking for a second that she may have been quite unlucky, but Spry buzzes correctly with armadillo so she (and I) can't feel too hard done by.

A full set of bonuses on maritime republics (called thalassocracies), which are not to be confused with hydraulic empires (which is a civilisation ruled by a monopoly on the water supply, like in Mad Max: Fury Road), gives Imperial (another word relating to empires) a 30-point lead. This quickly becomes 55 thanks to Salamanca Camacho and a hat-trick on mythology.

Spry buzzes on the next starter and pulls a face like he thinks he's screwed up, but his guess of Kissinger is correct, and it is allowed by Rajan who lightly scolds him for the slight delay in answering. They finally drop a bonus, giving Versailles instead of Paris, and Easow follows this up by dragging Manchester out of the negatives with theravada.

Sign up for The University Challenge Review

Could this be the turning point in the match?

Spoiler - it was not.

Manchester lost another five points thanks to a precocious buzz, and Elkouby picked it up to reaffirm Imperial's control. Spry's third put the London side into three figures, and they continued their charge from there.

Imperial are looking ominous at this point, which is perhaps unsurprising given their recent pedigree in this competition. Because while they have only won one more title than Manchester, three of their five wins have come in the past five years, while Manchester haven't won for eleven years. And indeed Manchester's semi-final appearance last year was their first at that stage since their 2013 victory.

Which makes Manchester the fallen giant of University Challenge, with Imperial rising to challenge their dynastic run from 2006 to 2013 in which they never failed to make it to at least the semi-finals.

No Mercy

Going into the music round, Imperial hold a lead of 140 points. Manchester's only hope is to squeeze their way into a high-scoring loser spot, but that would be possible only with the help of Imperial, who show no signs of letting up. Spry turns to Salamanca Camacho, clearly the classical music expert of the team, and he buzzes confidently with Rhapsody in Blue to take the starter.

The man from Madrid brings up Imperial's double-century, before Easow wakes Manchester from their slumber with Walt Whitman. It was going to take a huge effort to even break into triple figures from here, but Crossley wasn't going to give up with out a fight, taking their second consecutive starter with Congo.

Imperial 310 - 75 Manchester

Its early, but Imperial look like one of the teams to beat again this year (along with their fellow 300-ers Bristol). Manchester can count themselves unlucky to have come up against such a juggernaut. At the very least they managed to add one more appearance to their existing record, which Imperial are coming for.

Join me next week for Reading (19 apps) vs Exeter (24 apps), and subscribe if you haven't already for more excellent data analysis.

[tpointtechedu]

The Complete R Programming Tutorial for Aspiring Data Scientists

In the world of data science, the right programming language can make all the difference. Among the top contenders, R programming stands out for its powerful statistical capabilities, robust data analysis tools, and a rich ecosystem of packages. If you're an aspiring data scientist, mastering R can open the door to a wide range of opportunities in research, business intelligence, machine learning, and online R compiler.

In this complete R programming tutorial, we’ll walk you through the essentials you need to start coding with R—from installation to basic syntax, data manipulation, and even simple visualizations.

Why Learn R for Data Science?

R is a language built specifically for statistical computing and data analysis. It is widely used in academia, finance, healthcare, and tech industries. Some key reasons to learn R include:

Open Source & Free: R is completely free to use and has a vast community contributing packages and resources.

Built for Data: Unlike general-purpose languages, R was designed with statistics in mind.

Visualization Power: With packages like ggplot2, R makes data visualization intuitive and beautiful.

Data Analysis-Friendly: Data frames, tidyverse, and built-in functions make data wrangling a breeze.

Step 1: Installing R and RStudio

Before you can dive into coding, you’ll need two essential tools:

R: Download and install R from CRAN.

RStudio: A user-friendly IDE (Integrated Development Environment) that makes writing R code easier. Download it from rstudio.com.

Once installed, open RStudio. You'll see a scripting window, console, environment panel, and files/plots/packages/help panel—everything you need to code efficiently.

Step 2: Writing Your First R Script

Let’s start with a simple script.# This is a comment print("Hello, Data Science World!")

Hit Ctrl + Enter (Windows) or Cmd + Enter (Mac) to run the line. You’ll see the output in the console.

Step 3: Understanding Data Types and Variables

R has several basic data types:# Numeric num <- 42 # Character name <- "Data Scientist" # Logical is_learning <- TRUE # Vector scores <- c(90, 85, 88, 92) # Data Frame students <- data.frame(Name = c("John", "Sara"), Score = c(90, 85))

Use the str() function to explore objects:str(students)

Step 4: Importing and Exploring Data

R can read multiple file formats like CSV, Excel, and JSON. To read a CSV:data <- read.csv("yourfile.csv") head(data) summary(data)

If you're working with large datasets, packages like data.table or readr can offer better performance.

Step 5: Data Manipulation with dplyr

Part of the tidyverse, dplyr is essential for transforming data.library(dplyr) # Select columns data %>% select(Name, Score) # Filter rows data %>% filter(Score > 85) # Add new column data %>% mutate(Grade = ifelse(Score > 90, "A", "B"))

Step 6: Data Visualization with ggplot2

ggplot2 is one of the most powerful visualization tools in R.library(ggplot2) ggplot(data, aes(x = Name, y = Score)) + geom_bar(stat = "identity") + theme_minimal()

You can customize charts with titles, colors, and themes to make your data presentation-ready.

Step 7: Writing Functions

Functions help you reuse code and keep things clean.calculate_grade <- function(score) { if(score > 90) { return("A") } else { return("B") } } calculate_grade(95)

Step 8: Exploring Machine Learning Basics

R offers packages like caret, randomForest, and e1071 for machine learning.

Example using linear regression:model <- lm(Score ~ Age + StudyHours, data = students) summary(model)

This builds a model to predict score based on age and study hours.

Final Thoughts

Learning R is a valuable skill for anyone diving into data science. With its statistical power, ease of use, and strong community support, R continues to be a go-to tool for data scientists around the globe.

Key Takeaways:

Start by installing R and RStudio.

Understand basic syntax, variables, and data structures.

Learn data manipulation with dplyr and visualizations with ggplot2.

Begin exploring models using built-in functions and machine learning packages.

Whether you're analyzing research data, building reports, or preparing for a data science career, this R programming tutorial gives you the solid foundation you need.

For Interview Related Q&A :

Happy coding!

[storkmuffin]

I apparently hit the total number of links I can put on a tumblr post? Or something else is wrong. Anyway.

MASTERLIST PART 2 (updated 25.4.2)

San: Magic of San Part 3: The Marilyn Monroe sidebar 1. Magic of San Part 4: Marilyn Monroe Sidebar 2 Dumb? Magic of San Part 5: Marilyn Monroe Sidebar 3: Performance Intelligence & Humor. Magic of San Part 6: Marilyn Monroe Sidebr 4: On/Off and Studiousness, Why does San Speak in Pout. A long discussion of San in the Yeosang Essay

Seonghwa. Always fascinating. Hwa I'm sorry I'm like this (pun post) It was fate. Riverdalians for Seonghwa.

Wooyoung: I made my first gifset ever for Sagittarious, 영부인 really live up to their name. Late to the Long Hair Train Baby Woo Being Manly. Long discussion of Wooyoung in the Yeosang Essay. I love him so much that I listened to him chew for an hour

Yunho: master of the push-slap. The Mingi/Yungi post had a lot of Yunho thoughts. Yunho the Taker portion of Yungi Part 2, below. The Ateez Rosary Yunho Era Begins Yunho's Way of Using Lives #1

Yungi: Part of the Mingi Series but we can't not talk about Yungi. Yungi Part 2 - Mingi the Giver Yunho the Taker, Influence Yungi had on Woosan formation in the Yeosang Essay.

Mingi: asking the mingi ults what to cover. Why is this guy an idol and how. Yungi Discussion 1. Yunho is Bad for Mingi Thesis which is the same as Mingi the Giver Yunho the Taker. His Career Prior to Ateez. Support for my being 'off piste' about Mingi, Mingi stan rude ask, Blanket response to multiple Mingi stans How to Get Mingi Into Tight Pants. Naomyun kkendanikka explained Mingi MVP of the Seoul Encore 2025 Concert

Woo v Mingi: The neverending drama.

Jongho Being the one to send Mingi out alone.

Yeosang: The Yeosang Tragedy Series Part 1: Why are people fans of anything & What is it like to grow up a trainee , Part 2: How Yeosang Was PC but Lost Wooyoung. Part 3: What Can the Ateez Lore Reveal about Yeosang. San and Yeosang Yeosang and Beautiful People Problems.

Writing of others re: Yeosang: Phone Drama , The Christmas Live, A Yeosang Thesis with a focus on music

HongJoong: First Time I give him some thought

Korean Lessons: 요정 v 선녀 예쁨 v 잘생김 Continuing Korean Studies for the Native Speaker What is 존댓말 (short answer) The Mistranslation Problem The Mistranslation Example

Bias/ Wrecker/ot8: The difficulties of choosing a bias They are the pirates of Penzance to me Beauty Contest Between the Members Ask

K-atiny: The Lust Postings Dong-a Woman Media Coverage from 2023. Dress Code for Finale Concert Announced.

Buying more stuff: What is a platform album.

Neurodivergence discussion continues: What I get out of thinking of Ateez as ND.

Kpop Industry thru Ateez Lens: Ateez Debuted with 60 groups, Father Ateez Interview, KQ Finance Stats for 2022-23.

I started taking Kpop dance class: Class one. Class two. Class three. Class four

Towards the Light: Will to Power Tour Seoul Finale March 2025: The attendance guide arrives. Getting Ready for the Concert Concert attendance instructions in a low trust society. Day one I arrive at venue I attempt to buy a Lightiny at Venue Lightiny Sells Out Day one Post Lightiny Purchase fail Day One Liveblog 2 Day One Right at the Start Day One Write Up Part 1 Day One Write up Part 2 Second Day Pregame Liveblog Second Day Write up 1 Post Concert: What Changed?

Your Fantasy Tour: It came too soon?

On Shipping: I get it even if I don't do it. Why Fandom Gets so Dogmatic

The music: Fave song ask

Writings of others: Hwa the ASMR stan. Fayet's Cologne Series: 1 , 2, 3 ; a Write up of the Berlin concert! DO READ Fayet's write up of the dancing by the twin towers in an ateez performance - it will teach you how to watch dance. Detailed write up of the Brussels finale from a special Atiny who also went to the Amsterdam concert! Astrology of Mingi! Astrology of Yunho! Analysis of Woosan Lore & Persona! San and his search for a scene partner Wooyoung Winning Over Metalhead Dad Feminism Tarot Reading Cup Sleeve Club!

A fellow Tumblrina I met in person wrote up her concert experience for the Seoul finale!

Essays about Ateez (a masterlist- ongoing)

because no parasocial kpop obsession is complete unless you throw thousands of words at it. ) (Updated 25.2.17)

Seonghwa: I went off about Seonghwa & Queerness to start. Which led to follow up 1. And another follow up question this one about Jongho (mentioned in the first post). An ask about the general perception of Hwa. The magic of how he speaks. How he is out and yet not. How he gentle parents stalkers. Eventually I wrote a giant thesis about Seonghwa's Idol Persona. I manifested the finger suckage. Fingers in his mouth.

Is Matz 'real'? part 1. Part 2. The Lego Liveblog (Lego Queer King Dungeon)

Wooyoung: 입덕요정 Idol vs Real Manly man. Manly man part 2. Manly man part 3. Manly man part 4. Manly man part 5. His 형아미 Manly man debate continues. Etymology of 영부인 fandom name. Strong candidate for bias. Analysis of his dancing. His tattoos. His post Ateez career.

Side discussion about Minsung (Stray Kids) Brief Han Mention in context of Babygirling.

Short discussion on Ateez lyrics being advanced Korean,

Mingi. The Hippo Live. Mingi's Sound and Dance. His When Aliens Attack Live. His Don't Oppa Me Live. Liveblog of Mingi's song reveal live for untitled. Follow up to live blog. Is he ND. Mingi talking about Yunho's role in his life. Mingi the old testament prophet.

Yunho: his alleged 병크. follow up to the 병크. Yunho's beauty & appeal part 1. Catholic Hottie. The Magic of Yungi (Yunho Diction Focus)

Hong Joong: Leadership style.

San: In context of Woosan Tattoo. The Magic of San Ep 1. The Magic of San Ep 2: Men Crying, and the Gyeongsangdo Accent.

Kpop Dancing. As a ballet fan. Wooyoung focus. Hongjoong and Seonghwa as dancers. The older greats.

Kpop Idoldom: To be pitied or no? First discussion (failed) on kpop values. Do I think Idols fuck around? Aegyo 애교 and its discontents. Pity for the Hardworking kpop Trainee (or not) The Inevitability of Shipping & Boy Idols all Grown Up

How I stopped fearing being identified with Kpop fandom and became a fan. Saseng discourse. Authenticity and kpop. Comparison to soccer hooliganism

I started buying stuff. The first CDs (The Golden Hour Part 2). The first Set of Merch Unboxing.

Ateez as a known unknown band. My first impressions of Ateez. The effect each member has on me (unhinged post). Analysis of intragroup relationships. Leader and Maknae Relationships in general. Sorting the members into Hogwarts. Tour 2025 Flail. Unhinged thoughts about making members fight etc. Each Friend Group Has... Ateez on Korean TV?

Fan Service/ Queerness: A short discussion about 'fanservice' type queerness in kpop. More on 'seeming' gay. Speculation (or not) about individual members' queerness. Queerness in the arts & legal research. 7 ways to view BL fanservice.

Kpop Industry: KQ's Status or lack thereof. Boys vs Girls. Hybe v Min Hee Jin controversy. BTS As the Key Turning Point of Korean Pop Culture History. My thoughts on Virtual/AI Idols. Who are the 경상도 Idol?. Shinee Fandom Story.

Ateez & Neurodivergence. Discussion 1. Focused on Mingi.

Towards the Light: Will to Power Tour 2024-25: I got tickets to the Seoul Finale! It didn't sell out immediately in Seoul. Responsible Ticket Delivery.

Writings by other fans: Eye witness account from Amsterdam! Eye witness account from Zurich! Concert Experience also from Amsterdam. San is Born To Dance!

I recommended some books and films. Music I love. More books

[opens-up-4-nobody]

...

[retrowhatever]

All the Horizon Fanfic Stats You Never Knew You Needed

So I did some data analysis. More graphs and lots of rambling below the cut.

I love graphs. And spreadsheets. And making my hobbies unnecessarily complicated. So obviously once I discovered that there's an unofficial ao3 api, I had to learn a new programming language so I could throw some math at my Horizon hyperfixation and make some graphs about fanfics. This post is the result of that rabbit hole, I hope you enjoy it!

Before we get started, I want to make one thing explicitly clear: this post is a celebration. It's a celebration of fanfic, authors, and the fandom in general. If you have something mean to say about a ship, a writer, or a fic, this ain't the place. I made these graphs and wrote this post as a love letter to a game I'm obsessed with and the incredible people who make the fan content that is my main form of sustenance these days lol, so let's keep the discussion positive.

One last thing: I generated these graphs from data that I pulled on Aug 4, 2022. Anything published after that won't be reflected here. Alright, here we go! Let's see some graphs!

Fanfic by Length

The first thing I wondered is what the average length of fic was. I did not include any fics below 100 words, assuming they were either art or placeholders, neither of which provide any useful information regarding number of words.

I defined the categories as follows:

Ficlet - less than 2000 words

Short Story - 2K-10K words

Novella - 10K-50K words

Novel - 50K-100K works

Behemoth (pun fully intended) - 100K+ words

Obviously, there's some blurriness at the category edges, but it's pretty clear most fics tend to be relatively short. I'm genuinely surprised by how many huge, sprawling works there are though - I definitely expected there to be a single-digit number of behemoth fics. Mad props to the folks writing those monstrosities for the rest of us to enjoy!

Fanfic by # of Chapters

This graph kind of underscores the point about most fics being relatively short. There are almost twice as many single chapter fics than all other fics put together.

A thing I think is relatively unique to fanfic as a medium though, is that a fair number of those single chapter fics are novella or even novel length. You're not often going to find a book at a bookstore that's tens of thousands of words and has no chapter divisions, but that's not unusual in fanfic.

Fanfic by Author

Okay, the first thing you need to understand about this graph is the following numbers:

1

2.6

Those are the median and mean fics published per author in the Horizon fandom, respectively. In case you slept through your stats class, what that means is most fanfic writers have written one or two Horizon fanfics. Now go back and look at the graph.

...yeah. We as fanfic lovers owe a lot to these folks. Most of them are on tumblr, so even if you don't have an ao3 account (same, babe, same) you have no excuse not to go show them some love!

Serie11 is @valaloy

SoupAndChaos is @soupandchaos

mythicait is @mythicaitt

DragonRose35 I couldn't find a tumblr for

Kittleskittle is @kittleskittle

VidalsQueen is @sun-and-shadow-aloy

NorthernGhost is @thatsgonnabeanogho

sunspot (unavoidedcrisis) is @sunspott

januarys I couldn't find a tumblr for

foibles_fables is @foibles-fables

unstable_grad I couldn't find a tumblr for

Pikapeppa is @pikapeppa

YoGrossDude is @yogrossdude

bioluminesce is @owlswatch

wandereringray is @wandereringray

escafiils is @chloefraazers

Fanfic by Rating

Okay, now things are getting spicy! First of all, if I'd had to guess the most popular rating, it probably wouldn't have been Teen. But, given how popular the "fluff" tag is (foreshadowing for the tag graph later in this post), I guess it shouldn't be that surprising.

Secondly, I'm clearly not the only one who struggles to understand what exactly the Mature rating is for, considering it's the least-used rating by a fair margin.

Fanfic by Ship

The most popular ships, colour-coded based on orientation. From left to right: mlm, straight, wlw, poly, machines(?????), unknown

I want to reiterate here that I made this post to celebrate the awesome Horizon fandom, so if you're thinking of using this graph to argue that one ship is better/more correct than another... just don't, k? Good.

I also combined similar tags, so if someone used all three of the tags "Aloy/Erend", "Aloy/Erend (Horizon: Zero Dawn)", and "Aloy (Horizon: Zero Dawn)/Erend (Horizon: Zero Dawn)" for the same fic, that's actually going to count as three fics in the Aloy/Erend column. I'll probably end up redoing this graph eventually with a less naive counting algorithm, but for now this is what we've got.

Now that we've got methodology out of the way, let's talk about some cool things this graph shows!

First, Kotaloy shippers obviously have a lot of things to say. Unlike the other five most popular ships, Aloy/Kotallo is the only one involving a character that wasn't in the first game. And it's the second most popular ship! Y'all are rabid and I love it.

Second, of the wlw ships, the second and third most popular ships involve a character from the DLC and a character who dies immediately after you meet her, respectively. You guys are out here making meals from crumbs and I am impressed. Also, though, why don't Petra and Vanasha get more love??? I'm unsurprised that Talanah and her favourite Thrush are the #1 ship, but I (a clueless straight, to be fair) loved both Petra and Vanasha and definitely expected to see more fic involving them.

Third, I love the variety here. This graph only includes ships with at least 10 fics, and there are so many different ships represented! There were tons more that had 5-10 fics too, and it honestly made me so happy to see that there were multiple fic options for almost any pairing in the game.

Fanfic by Tag

Y'all. Look at all the fluff. People always joke about making their blorbos go through it in their fanfic, but like. There is SO MUCH FLUFF. We all really just looked at these characters and went "well, they deserve nice things for a change", huh? I also love how popular canon divergence is - anecdotally, I usually see that tag on fics that are like "well, what if that shitty thing didn't happen?"

That's not to say it's all sunshine and rainbows. The next two most popular tropes are "angst" and "hurt/comfort", and as an enthusiastic consumer of both, I'm not surprised. But again, anecdotally I see a fair number of fics tagged with one or both of those and a "fluff" tag.

Going back to the ratings graph, where we learned that the most popular fic rating is Teen & Up, it shouldn't be surprising that both "First Kiss" and "First Time" are more popular tags than any of the more explicit sex ones. Also, given that Aloy grew up an outcast, I think the popularity of those tags speaks to how fun it is for both writers and readers to delve into what that means for her when it comes to sex and relationships.

Finally, the most-used content warning tags will surprise exactly no one, I think. Canon-typical violence (because duh), PTSD (growing up a literal outcast before finding out you're a clone made by an AI so you can save the entire world from extinction will do that to ya, not to mention all the shit Aloy's friends/lovers have been through in their own lives), and canonical character death (glares at GEMINI) are all pretty obvious choices.

Conclusion

Because I have zero impulse control, I'm already working on a part two for this post, where I will address such pressing questions as "Which ship has the most verbose authors?" and "Who's the gayest Horizon character?" as well as recklessly use the powers vested in me by the math and algorithm gods to find some hidden gem fics that you might not have read yet.

In the meantime, I would love to hear some more opinions on these graphs! I've commented on some of the things I found interesting, but there's lots more to address here, so feel free to reblog this post or snag any graph you find interesting to use in a post of your own. I only ask that you tag me if you do - because I want to read what you have to say!!

Also, if there's any stats or questions about Horizon fanfic that you're particularly curious about, let me know. I'm limited by the information available on ao3, but I will do my best to find you answers and include them in the next post.

Lastly, one final reminder that we're here to celebrate the awesomeness of Horizon fanfic, the fanfic authors, and the fandom in general. I will humbly accept all constructive criticism about my (somewhat questionable) statistical methods and data interpretation, but ask that you keep comments about ships, tags, authors, etc positive and productive. Remember these are real people creating free content for the rest of us, and don't yuck someone else's yum.

Thank you for reading, and I hope you found this half as interesting as I did!

[fffinnagain]

10 Years of Sherlock (TV)  AO3 stats!

Sherlock fans, new and old, click below to read a long list of graphs and comments about our communities fanworks over the last 10 years. I scraped AO3 again and demonstrate that:

More creators are writing longer works in 2020

Readers engaged more as the fandom changed after S4

Top ten new tags per year for the last 10 years

And a lot more. 

PS the code to gather this data and analyse it can be found way over here. 

Activity over 10 years

The last 10 years in the BBC Sherlock fandom have been tumultuous, but this community persists, with engagement from new fans and continued creative output. To commemorate over a decade of squee, I’ve done another scrape of the fandom’s imprint on the Archive of Our Own and will share some insights from the numbers in these plots. A very late update on my post S4 snapshot from 2018.

Note: This analysis is of completed public fanworks only, about 101000 of the 122000 Sherlock (TV) works available at present. This is to remove the late WIP effect, which adds a bulge to the last few months, and out of respect to creators who wish to have their material reserved for other registered AO3 users.

The works are still coming

Counting the number of works posted per day, we can see the peaks associated with each series airing (in UK and US). After that, the number of works continues fairly evenly, 20-30 per day, plus seasonal peaks. This rate is continuing on without a hint of new canon in sight. So who is posting all this work?

Creator-waves, monthly output

Years ago I started plotting creator waves, basically I group fanwork producers by the year they first posted to the fandom and then count how many of this group are active in later time intervals. This lets us get a sense of how long people are contributing and whether new fans are getting the urge to create. 

This plot of the Sherlock (TV) fanworks on AO3 shows the standard shape of plump participation in the first year of any given set of creators, followed by a slowly thinning tail as they because less active over time. Turnover is natural in fandoms, with most only posting a work or two within a fairly limited amount of time, while a precious few persist for years.  The surprise for me here is that the ratio of new creators is higher in 2020 than it was in 2019. Maybe the excuse of lockdown encouraged more folks to take a turn at creating content. 

Another way to look at the output of fan creators on AO3 is to see the total amount of words being shared across all fanworks. The total has been pretty close to 300-400k words per month since 2018! To get a sense of what that means per work, I also plotted the median number of words per fanwork in these monthly sets. The median in higher in the last year than it had been staying for a while. 

Reader behaviour: Hits & Kudos & Comments

Fan creators are only part of the story. Stats on engagement are a bit trick to interpret, I’ve got some plots here that tell us something about how works have been engaged with over time. 

The obvious first to consider is Hits. Above is the total number of Hits given to works published each month. This is the current totals, not a historical snapshot, so we have a very strong bias  towards early works, what we might call the Classics Effect. Works that have been around longer have had the chance to be seen by more people, and in particular those works that become must-read classics in a fandom, extending their exposure through prominence in top ranked works and recommendations. 

To cut down on the advantage of the classics, we can also consider median hits per work for each month. As most works get a lot attention when they are first posted and then fade out of sight, the median number of hits reflects instead the ratio of readers to creators, basically how many eyeballs are around to look at the latest work, regardless of status. The median plot shows how the hyper-visibility of the few work available before 2012, and then a more steady curve once the fandom had gotten established on the platform after Series 2. Amazingly, the hit rate for the median work was steady through the big bumps in activity with later series, a 1000 hits for median works between 2013 and 2018, followed by a slow decline. I’d expect the 2020 works to continue gaining for a few months yet, but the median is probably 50-60% of what is was when the show was in production.

Kudos counts and medians show a similar story to hits, but there is a dip down around 2013 for kudos reflects the frenzy of productivity that saw the fandom grow during the Series 2 hiatus. Readers were getting spoiled! From the airing of Series 3 (2014) until a year following Series 4 (2018), the median work received an even 60ish kudos and 1000 hits, a niche audience that decreased to 50/750 through 2018-2019. The numbers of 2020 suggest a smaller community of readers again, though these numbers may still rise a bit in the next few months before the median works are forgotten. 

The statistic that tells a different story is Comments. Looking at the total comments counts, there isn’t a drop after Series 3 (2014). Instead, the fandom compensated for changing numbers with more feedback and discussion attached to works. This is reflected in the median comment rate as well, which shows seasonal variation but doesn’t really drop off until 2020.

It’s remarkable that without fresh canon we continue to have new creators contributing to the fandom, and while that may be outpacing the readership somewhat, the standard of engagement has been very high. One could say the fandom is chugging along quite nicely!

What about Tags

So, with all that turnover and shifting population, is there a change in the kinds of works being posted? We can look at tags, all tags and freeform tags, to see if there were any meaningful trends. 

First up, I did a creator-wave like analysis of works just for tags, to see how tags continue to be used after being introduced. Unlike the creators, tags clearly persist for years. After 2015, it looks like the core tag set has been established, with very few tags persisting in usage per  subsequent year.

This graph reports numbers over time that are not proportional to the number of works or creators active. Instead, works on AO3 have been getting more and more tags over the years, with the average steadily growing from 5 in 2011 to 15 in 2020, with freeform tags (not characters or ships) from 2 to 8.

To get a sense of fic and tagging culture changes over time, I counted the most popular NEW tags of each year (wave). Note: this analysis is using exact matches, not the networked associations of tag meanings wrangled into AO3 today, so some things that pop up aren’t new concepts but instead newly popular TAGs for whatever they represent. 

2011: 2752 (First year, so all solid stuff, tags that continue to be popular forever)

Angst                 323

Fluff                 232

Humor                 216

Hurt/Comfort          188

Romance               168

Friendship            168

Crossover             138

Crack                 121

Alternate Universe    119

First Time            106

2012: 11637 (still early, first references to Series 2)

Fluff and Angst                           145

Episode: s02e03 The Reichenbach Fall       97

Kid Sherlock                               54

Puppies                                    50

Sad                                        48

Episode: s02e01 A Scandal in Belgravia     47

Mathematics                                42

Season 2 spoilers                          38

Omega Verse                                38

Feels                                      38

2013: 16176 (Omegaverse nomenclature is growing, Top/Bottom terminology, new challenges)

Alpha Sherlock                               65

Omega John                                   61

30 Day OTP Challenge                         59

Tumblr: letswritesherlock                    56

Top John                                     49

Sherlock Holmes Returns after Reichenbach    44

Bottom Sherlock                              40

Reichenbach Angst                            30

Don't copy work to another site              29

Age Regression/De-Aging                      27

2014: 19256 (Mostly Series 3 related

Episode: s03e03 His Last Vow         249

Episode: s03e02 The Sign of Three    167

Post-His Last Vow                    149

His Last Vow Spoilers                142

Sherlock Series 3 Spoilers           128

2000 AU                              100

The Sign of Three Spoilers            74

Fatlock                               72

Post-The Sign of Three                66

Post-Season/Series 03                 57

2015: 14272 (New challenges, new prominent Sherlolly tags)

Chats                                      47

International Fanworks Day 2015            34

Watson's Woes July Writing Prompts 2015    27

S3 referenced                              25

Sherlock Holmes/Molly Hooper Kissing       22

English Accent                             22

Sound cloud                                19

Eventual Sherlock Holmes/Molly Hooper      19

Protective John Watson                     18

but not that kind of graphic               17

2016: 13517 (New stylistic tagging, TAB references, a lot of epilepsy?)

Slowwww burn                         92

John Watson Loves Sherlock Holmes    37

Sherlock Holmes Loves John Watson    33

post-tab                             30

JME                                  27

Post TAB                             25

Juvenile Myoclonic Epilepsy          23

Sherlolly Appreciation Week 2016     19

epileptic                            19

fraternal love                       17

2017: 15067 (Series 4 tags and challenges)

Episode: s04e02 The Lying Detective         133

Episode: s04e01 The Six Thatchers            93

Post TFP                                     73

Sherlock Series 4 Spoilers                   69

Episode: s04e03 The Final Problem            60

Post-Episode: s04e02 The Lying Detective     55

Sherlolly Appreciation Week 2017             50

Post S4                                      48

Sherstrade Month 2017                        44

31 Days of Porn Challenge 2017               41

2018: 10733 (Lost of new challenges, seasonal and weekly)

Towel Day 2018                       64

Mystrade Valentines Calendar 2018    25

Kinktober 2018                       23

Pregnant Molly Hooper                23

Soft Smut Sunday                     23

Tom Robbins                          23

Sherlolly Appreciation Week 2018     21

Inktober 2018                        20

established universe                 16

Always1895                           16

2019: 7785 (More prompts, and character attitudes)

Sherlolly Appreciation Week 2019    25

221B Autumn Challenge               21

A-Z Christmas Prompt                19

KatsJohnlockXmas2019                16

Whumptober                          11

Poor Greg Lestrade                  11

Kinktober 2019                      10

Dissonance                          10

John Watson is a Good Friend         9

Sleepy Sherlock Holmes               8

2020: 8074 (Not all COVID related, thank heavens)

Mystrade Monday                           59

COVID-19                                  48

Coronavirus                               46

Mystrade Monday Prompts                   40

Whumptober 2020                           36

warning for a covid-19 setting            33

Flufftober prompts 2020                   24

Do Not Translate                          24

they're all right they're just at home    23

Granada Sherlolly                         21

A little note from looking across all freeform tags, not just the new ones, we see a curious pattern with regards to two actions: First Kiss and Anal Sex. They appear amongst the most common tags as of 2014, neck in neck for two years, than Anal Sex drops off the top ten in 2016. From there out, First Kiss stays in the top 5 from that point on, while anal sex appears at rank 9 from 2017-2019 and is gone again in 2020. This probably says something about the fandom, somehow. 

Bravo for making it to the end and thank you for reading! 

Questions/comments welcome.

[roundedloaf]

Murderbot Fandom Statistics May 2021

On the 19th of May I scraped the #introductions channel of the Murderbot Diaires 2.0 discord, and StellHex ( @hextrudedcubes​) scraped the Murderbot tag on Ao3. Analysis below the cut!

Archive of Our Own Statistics:

[ID: A line graph of the number of new works in the Murderbot Ao3 tag per fortnight. Overlaid are the release dates for each Murderbot book, the start date of the Murderbot discord and the creation of the discord’s #event-despair-horizon.]

[ID: A bar chart of the total number of Murderbot Fics on a weekly basis.]

There was a significant delay between the release of All Systems Red and it’s first fic being written. After that we see that the number of fics per week increases steadily after the launch of the 2.0 discord server. This is likely a mixed effect between the supportiveness of the 2.0 server for encouraging writing and representative of the fandom growing steam more widely. In recent weeks >20 fics have been posted a fortnight.

The despair pit, a discord channel for discussing very angsty fic, is a known spot that fanworks come out of and fic writing increased around that time. (#event despair horizon).

On the 19th of May there were 289 fics in the Murderbot tag but only 280 are included in this analysis as 9 of them are locked to logged in archive users.

Shipping Tags:

Category | Number of works Gen         | 240 Other       | 30 F/F           | 2 F/M          | 1 M/M         | 1

Murderbot is not a shippy fandom. 85% of fic is tagged as ‘Gen’ compared to 20% on Ao3 as a whole [1]. A number of the ‘Other’ fics are tagged with Murderbot & ART (rather than Murderbot/ART), suggesting this fandoms deep love for “what ever those two AIs have going on” rather than romantic relationships.

The only relationship slash tags involving Murderbot are Murderbot/ART, Murderbot/Gurathin and Murderbot/Soap Operas.

The sole F/M fic is a Star Wars Relyo crossover. F/F and M/M fics involve either secondary characters or OCs.

Discord Introductions:

[ID: A line chart of the number of users who mentioned themselves in introductions per day. Dates a labled for the start of the server, Verso and Anrea sharing links, the start of the despair pit and the release of Fugitive Telemetry.]

The Murderbot diaires 2.0 discord started after it was clear the previous discord had been abandoned by it’s mod. The start day had the largest number of people joining the server, and the second largest peak was due to the initial sharing of the join link on Verso’s ( @grammarpedant) tumblr. We can also see that fandom momentum picks around March this year and around Fugitive Telemetry’s release date.

This data isn’t super clear so I’ve also computed the rolling six day average below which makes the increasing number of new users recently more apparent.

Of the 410 server members 311 (76%)  introduced themselves. Introducing yourself is optional, and this is due to a mixture of lurkers, people checking out the server and not leaving, and people who felt too awkward or just didn’t want to introduce themselves.

Total number of introduced members:

Methodology Notes:

Ao3 fics were webscraped by StellHex who used the ao3_api tool.

The count of #introductions was webscraped by me using Discord Chat Exporter. I then counted the first instance of a user speaking in that channel as their introduction.

Analysis was completed using numpy/matplotlib.

Final Notes:

If you want to join the discord you can do so here.

I’m happy to send the code and data I used for this analysis. I’ll post it on discord, or flick me a message there if you can’t find it.

In future it would be cool to do an analysis of the emoji usage in #fanworks-gallery and #introductions.

References:

[1] toastystats (destinationtoast),  [Fandom stats] Shipping on Wattpad vs. AO3 and FFN (https://archiveofourown.org/works/18721183), Published 2019-05-05, Retrieved 2021-05-26

[sickcyclist]

This is the story of my day. It actually starts yesterday, when a heaven-sent rain swept in and cleared the smoke and cooled the air and tamped down the dust on the trails. I went on a bike ride because days like that are a gift. I have exercise-induced hypoxemia, which basically means that my oxygen drops when I exercise for reasons that we still don’t understand. Exercising with oxygen helps, but I still drop into the mid-80s. I knew I was too sick to ride and that doing so would make me much more sick, but I needed it for my mind so I was willing to sacrifice my body.

So that’s the first lesson of being sick. Everyone tells you that you have to be active and it will make things better and all you have to do is just push yourself hard enough. We’ve internalized this message to the point that many people believe sick people could get better if they just PUSHED. But that’s not always true. Sometimes pushing makes you worse. Sometimes it makes you much, much worse. And that can be true even if being active and pushing hard is something you love so much that it feels like it’s core to who you are.

I knew I would have to sleep for 12+ hours to make up for the ride, and I knew that I would have bad oxygen saturation stats because of it. And since I don’t have a real job, it should be easy to just take a lazy day (or week, or month) and get better, right? But actually I do have a real job and that job is to keep myself alive. It’s the job of a lot of us who are chronically ill, and it’s not a profession I would recommend. It’s not fun and it’s not rewarding and no one admires you for it and you’re not asked to speak to 5th graders on career day and you rarely get to move on to a newer, more interesting project.

Here’s what this particular day at work looked like for me. I woke up to a voicemail saying that my pulmonology appointment for Friday had been cancelled. I’ve been waiting to see a pulmonologist since March and was supposed to have an appointment weeks ago, but that was cancelled because the doctor quit two days beforehand. The other doctor in town couldn’t see me until the end of October, so I looked for a doctor in a bigger town hundreds of miles away. She comes highly recommended and in a way I’m happy because I strongly prefer female doctors, but for whatever reason she had to “clear her morning.” My new appointment is five weeks from now. I got off the phone and sobbed, which is not a good thing to do when your lungs don’t work. I probably could have toughed it up and avoided crying if I hadn’t worn myself down so much biking yesterday, but such is life.

I emailed my primary care provider asking for a note saying I could travel with my portable oxygen concentrator. I was supposed to get this letter from my pulmonologist, but now I won’t have a pulmonologist before I travel. The letter has to say that I use oxygen for sleep and activity, but it also has to specify that I won’t use oxygen on the plane. Which is a little funny because airplanes have extremely powerful oxygen-producing systems for emergencies, but they don’t like people who need oxygen because they don’t like the risk that comes with having sick people on board (think emergency landings). So people who need oxygen all the time need their own oxygen concentrator and battery power for the equivalent of 1.5x the time they will be in the air. I’m going on an 8-hour flight and it would cost about $400 to get strong enough batteries for that length. So I need them to let me carry my machine, which has lithium ion batteries that are otherwise prohibited. But in order to carry my machine I need to prove that I won’t be needing it.

I have a great primary care provider. I knew she would write the note. Easy peasy.

My next voicemail was from the specialty pharmacy that my insurance provider uses for certain drugs. I am allergic to a hormone all women produce as part of the menstrual cycle. This allergy is so severe that it has been responsible for 5 miscarriages, and it also means that I’m more miserable than usual for half the month. The good news is that all you have to do to stop it is take out your ovaries, but when you do that you go into full menopause. Which is not desirable because it increases your risk of cancer and osteoporosis and just overall mortality. Like not even from one thing. Just people who go into menopause early die early from all causes and we don’t know why.

That gives you some perspective on what the benefits have to look like in order for the cost-benefit analysis to still auger in favor of ovary removal. But since it is such a serious choice, you have to be sure. And the way you make sure is to stop your ovaries from working with a drug. The drug has hideous short and long term side effects, so if you feel better while taking it, that’s a pretty strong sign that an oophorectomy is the choice for you.

Approval for me to receive this particular drug was in limbo because the provider accidentally entered the wrong diagnosis. I have, as you can imagine, a lot of diagnoses. Entering the wrong diagnosis in this case was particularly funny because I’ve spent the last 6 months fighting with Blue Cross to get an expensive medicine that helps with my allergies. This medicine (Xolair) is approved for chronic urticaria (hives). It is not approved for progesterone hypersensitivity. I have both, which means I itch a lot for two weeks of the month and itch so much that I want to peel my skin off for two weeks of the month. Blue Cross argued that I wanted the drug for progesterone hypersensitivity. No medical provider said that, but it was the diagnosis they could use to deny the drug. Xolair costs $4000 a month. At that price it’s worth it to them to grind people down and hope they give up. It took four appeals and my lawyer (husband) to get the drug approved because I do indeed have chronic urticaria. It’s worked wonders for me, especially being allergic to the sun. You have no idea how easy it is to descend into madness when you are itchy all the time.

I went over all this with my new OB. I explained that, while the allergy shot solved the itching, it didn’t fix any of my systemic problems, which is why I was still interested in removing my ovaries. And because the conversation focused on how this ovary-suppressing drug (Lupron) specifically wasn’t for urticaria, it’s perhaps not surprising that she accidentally listed urticaria as the reason for the prescription. It’s like when you’re afraid you’ll mispronounce someone’s name. You tell yourself, “Say Kee-a, not Ky-a,” so many times that you’re basically guaranteed to call the person Ky-a.

So my ovary medicine was denied, of course, but I contacted my doctor’s office last week explaining the problem and they were very quick to apologize and resubmit. I returned the call from the specialty pharmacy but apparently they had just wanted to let me know that they were sorry for the delay. It was very polite of them but maybe didn’t require a phone call.

Then I got an email from Blue Cross Blue Shield. I logged in to read that coverage had again been denied (no reason stated) and that if I wanted to appeal the decision I would have to appeal through their specialty pharmacy. They gave me the name and number. Of a different specialty pharmacy than the one I had been dealing with for the past month. The one that I had already wrangled account numbers and diagnosis codes and special customer service phone lines out of. I typed up a polite response inquiring why I need to change pharmacies. And then I cried, but only just a little this time.

Then I called Walgreen’s because my medication for muscle spasms had been delayed and I received a note saying the pharmacist needed to speak to me. I am hypermobile so my connective tissue is just a little too bendy. My joints slip in and out all the time and my muscles have to overwork to hold my body together. Frequently they overwork so much that they lock up. This happens much more frequently in the progesterone-dominant phase of my cycle. Physical therapy is the best treatment, but sometimes I need muscles relaxants before I can even start physical therapy.

The man I spoke to at Walgreen’s told me I didn’t have a prescription for that drug. Then he told me I had a prescription but it had expired in March of 2020. I knew that wasn’t true because I hadn’t used it for years but had to start again when I got COVID. So I had no prescription in March of 2020 but I definitely did in March of 2021. No big deal. Just a simple computer error. Totally understandable in a pandemic, and I knew my doctor would refill it anyway. But he apparently felt that it was a big deal and wouldn’t submit the refill to my provider. I have no idea why. Maybe he thought I was engaged in drug-seeking behavior. Or maybe he was having a bad day. But he wouldn’t submit the refill. I hung up the phone and screamed. Loudly. Which really is not a good thing to do when your lungs don’t work.

Murry came up and rubbed the spasm out of my shoulder and listened to me vent and offered to be my medical power of attorney so he could deal with these people for me. But he’s the one with the real job that earns real money and when I’m sick he also cooks and cleans and does the shopping and walks the dogs. I may not be any good at the shitty job I had, but there’s no way I’m going to make him do it.

I switched tactics and chatted with someone through the Walgreen’s app. He was lovely and had no problem submitting my prescription for a refill. Easy peasy.

My final task for the day was calling to find out about the status of my CPAP prescription. I don’t have sleep apnea but while I’m asleep my breathing does slow down significantly enough that my oxygen drops (hypopnea). I need a special CPAP that adjust the pressure to my breathing, but it will get me off of oxygen at night. I’m very excited for it.

My insurance does not require prior authorization for CPAP prescriptions. However, St. Pete’s has its own prior authorization department that I guess makes sure you are not lying about not needing prior authorization? This department is, apparently, understaffed. I called my oxygen “rep” to find out how it was going. She very kindly bypassed the prior authorization department and called Blue Cross directly. Blue Cross informed her, as had I, that a prior authorization was not necessary. She could officially get me a CPAP.

Except that there is a national CPAP shortage. So she will try her best to get me one as soon as they get more. Hopefully this month. Even the rare, wonderful people who try to help you are sometimes as helpless as you.

I didn’t cry this time. Crying doesn’t fix anything and I can’t risk losing more oxygen. So I turned to writing therapy instead.

This was a bad day at work, but there are rarely good ones. It sucks to be sick, but I’m smart, articulate, overly educated, wealthy, and white. It could suck so, so much more. Someday I’ll turn all of this knowledge that I never wanted into something that helps people other than myself. Until then maybe someone will read this and know they are not alone. If being sick is your job, I see you. I would give you a hug—or a bonus!—if I could.

[unnamedelement]

Image description: The first image is a drawing of Gimli from the side. He sits at a table in the archives/library in Minas Tirith and is holding a piece of parchment in his [poorly drawn] hand. There is a sheaf of notes to his left, and a venn diagram similar to the one in Image Two is sketched on it. The second image is a picture of notes from a statistics lecture on multiple regression. There is a three-way venn diagram in the upper right hand corner and others notes scrawled about.

 I don’t usually draw because it is absolutely not at ALL one of my skills and talents--have you SEEN the beautiful things people create in this fandom?!--but I started doodling after a headcanon came to me during the last hour of my Stats class today, and it carried me away. So here is a picture of Gimli laboring in the library in Minas Tirith, poring through old lore about the elves and their ailments, in an attempt to lift the spirit of his friend in the only way he knows how. Also, please indulge me by reading a new headcanon I have about dwarves. Eventually I’ll be writing up this little concept into a one-shot spinoff of my WIP series At Sea in the Middle of Ithilien. 

Non-Spoiler Summary of the Series this Headcanon Orbits

You can find the At Sea series here (Part I) and here (Part II, the WIP). Most of my other writing about the sea-longing can be found at this link.   Please dear God, do not hesitate to talk to me on Tumblr, Ao3, or FF about the sea-longing. There is little in this Middle-earth I love more than exploring this concept.

Long and short of it, these stories take place around Fourth Age 30. Legolas and his elves--including his partner--are living in Ithilien while Gimli is in Aglarond. Legolas has been increasingly struggling with the Sea-longing, and the methods he and his friends have employed for years to curb it are running thin. Eventually, a tragedy of sort strikes, and it forces them all to take a new approach. Because Gimli has always been Legolas’ anchor in the midst of the Sea-longing, they begin the long labor of piecing Legolas back together.

And that’s where the headcanon comes in! Click below to read about dwarves and statistics and how Gimli tries to heal his favorite elf’s heart.

Basically, I decided that dwarves have an excellent understanding of mathematics and statistical analysis--beyond the understanding of even the Noldor in the Third Age--due to the limitations of their mortal lives. They are makers, creators, craftsmen, and builders, and they do not have forever to wait around to watch what happens, to piece together the patterns of things, and yet there is a drive and a fire to create. And, thus, for dwarves, math and formulas and statistics become a key and increasingly complex part of not just the designing of things but also the predicting of them. The dwarves collect data on a number of things, so they can answer questions like-- In what circumstances is a flood most likely to collapse a tunnel? What factors increase the likelihood of death during famine? Which jewels are most lucrative when brought in which seasons to which markets of Men? Dwarves are a sturdy people, but this self-created knowledge is part of what makes them so. So, after the War, Gimli brings these skills of his people to Minas Tirith and then, afterward, to the Glittering Caves--the planning and safety of these places, their structures and their beauty is rivaled only by the reliability of his work.  Thirty years pass and we are just past the time of At Sea. Gimli and Legolas travel together while he puts himself back together, and they follow Aragorn’s careful instructions on all those things that he thinks and he hopes--as a healer--are most likely to keep Legolas’ feet on the ground. But elves are not meant to resist the Sea, and they do not have much to go on but supposition and prayer.  But then Gimli begins to think. For, oftentimes, aren’t decisions made without all the data? Certainly there are not elves a-plenty to ask about the Sea here in the Fourth Age, he ponders, and there are none living save Legolas who are actively denying it, but surely there is information hidden about somewhere? There are archives in Minas Tirith, he muses, and libraries kept still by the Sons of Elrond in Imladris, after all... And if he can collect as much data as he possibly can from accounts of the past, might they not have a better idea of what things to expect, what things to avoid, and what things they might try to sooth his friend’s soul? For even if no elf in the history of the world resisted so long as his, there are probably hints hidden in all these millenia of writing that may open the door to improvement... And, so, when they return from their wandering, Gimli sets to it, for he is stalwart and stubborn and a solver of problems. He pores over texts and writes to Rivendell to ask they do the same; he recruits Faramir and Elboron to the project; he consults Arwen and writes to Mirkwood for whatever oral lore they may have stored away there in Wood-elven minds, and he works and works and works. He catalogues every possible example of Sea-longing and its effects and outcomes and the traits of the elves that have suffered it. He analyzes specific cases closely and uses them to guide the coding until he has buckets of predictors and traits and variables that might map onto outcomes and behaviors and feelings that he can just barely grasp, dwarven as he is, but that he hopes--if intervened on--might alter the course of things for his friend. So, eventually, Gimli has set to work with his formulas and his statistics, and he labors and calculates and checks and rechecks until he thinks he has some answers--he takes what he has found to Aragorn and Arwen, and eventually to Legolas and to his people. Then--after much time and much patience; some tears and much frustration; moments of failure and triumph and vulnerability and forgiveness--the stability of a new normal emerges, and it becomes a little bit more enjoyable and much more manageable for Legolas to move through a world in the Fourth Age of Men that is no longer built to accommodate elves. It is not perfect but it is enough. And that is the way that Gimli became the first dwarf in Middle-earth to labor so for the cause of an elf as to be named elvellon twice over. And it is also the story of how a dwarf became the first person in the history of their world to approach the healing of hearts in so logical a way that--nestled within the complimentary knowledge of those things beyond numbers--a new era of treatment was born. And all of this because a Dwarf could not bear to be parted from his Elf.

THE END

[slliest-clownmari]

Hello again! For the month of June we decided to don our best Icarus costumes because we flew directly into the sun on this one! Extra long disclaimer this time. If you're interested in the technical side what we did and how it went wrong, or want to see the raw numbers, that'll be at the bottom of this post!

Disclaimer: There were two major errors during collection. The first one resulted in five people's views not being collected for the first half hour of the event.  These people were SMajor/Noxcrew, ItsFunneh, Squaishey, ASFJerome, and Mefs, amounting to about 56k views when added back. The second error left a 45 minute gap in the data where nothing is collected. While these are major errors general trends are still visible and neat to look at!

TL;DR: MCCP21 peaked with 627.4k viewers a little more than thirty minutes into the event. 65.4% of those viewers were watching the Pink Parrots, and 87.9% of those were watching Technoblade. The second most watched team was the Lime Llamas at 16.9% of viewership, 77.6% of that coming from Wisp.

For easier viewing of the graphs, check out the Google Slides version! Total Viewership Over Time

The event peaked with 627,421 viewers at 8:33PM which was during Sky Battle. Looking at the trend of the data, this statistic is unlikely to have changed if the missing 45 minutes had been counted, especially seeing how the peak of MCC14 was also easily in the first hour.  Data collection began about an hour before the event's official start at 8:00PM and ended an hour after the event's end at 11:08PM.

Viewership by Individual Over Time

A fun game you can play with this graph, sans the labels, is guess which one's Technoblade! So far everyone I've shown the unlabelled graph to has guessed correct.

Three people went live after the official start time of the event at 8:00PM, those being Technoblade, Grian, and AyChristeneGames. Four streamers had gone offline prior to the end of 20vs20 Dodgebolt at 11:08PM. Twenty of the 24 participants had gone offline within 5 minutes of the event end. This is in sharp contrast to MCC14 where it took 15 minutes to have half of the 36 participants to go offline. MCC14 participants were also more likely to start streaming well in advance of the event. (For context, only Twitch data was collected for MCC14.) This is probably a cultural difference between Youtube and Twitch.

Viewership by Team Over Time

The viewership drop off after a team fails to reach Dodgebolt is a lot more severe this time, and you don't really see the two teams who did get to Dodgebolt get a boost either. Best guess is this is because MCCP21 was non-canon so nobody really cared who won the whole thing if their favorites didn't make it. Another observation: Pink Parrots has a much more severe dropoff during the Bird App Poll than everyone else. Unseen here is the viewership increase when Wilbur's fire alarm went off :(

Viewership Breakdown at Peak by Individual

So, not the most diverse viewership. The most watched person at peak in MCC14, Tommyinnit, only had 21.1% of total viewership. Even if you combine that percentage with the runner-up Dream's numbers, you only get 38.4% of viewership going to them. There is not a single team from MCC14 who captured nearly 57.5% of the viewership. The most they could do was 39.9% (Green Guardians). Absolutely insane degree of domination.

Top Five (Unrouned) 1. Technoblade (360.8k) 2. Wisp (82.2k) 3. Grian (45.5k) 4. ItsFunneh (44.9k) 5. Joey Graceffa (23.5k)

Bottom Five 26. Burren (78) 25. SeaPeeKay (333) 24. Spifey (403) 25. AyChristeneGames (498) 26. InTheLittleWood (521)

Wisp's numbers were so hugely different from last time (0.1% to 13.1%) that I actually sought out people who watched him to confirm he really had over 70k viewers. He did. This probably has to do with having fewer big names to compete with and being on a team with Tommy and Tubbo. Plus, he’s more familiar to the Minecraft community than Joey Graceffa, so fans of Tommy and Tubbo would be more likely to watch Wisp to see their faves. This isn't meant to belittle Wisp or to attribute his viewership entirely to Tommy or Tubbo; MCC is an unfair measurement of the usual popularity of a creator.

Viewership Breakdown at Peak by Team vs Survey Data

The predicted viewership graph was generated using data from a poll I ran on Tumblr and a poll run by u/Epic_Ninja_Dude123 on r/MinecraftChampionship.

Difference from predicted counts (Pred. % vs Actu. %) Lime Llamas: +9.1% (7.8% vs 16.9%) Green Guardians: +6.3% (0.9% vs 7.2%) Purple Pandas: -6.3% (6.7% vs 0.4%) Orange Ocelots: -5.1% (5.5% vs 0.4%) Red Rabbits: -4.1% (6.2% vs 2.1%) Blue Bats: -1.9% (2.5% vs 0.6%) Aqua Axolotls: +1.3% (2.5% vs 3.8%) Pink Parrots: +0.9% (64.5% vs 65.4%) Yellow Yaks: +0.5% (0.0% vs 0.5%) Cyan Creepers: -0.3% (3.2% vs 2.9%)

Standard Dev. for MCC14: 10.22 Standard Dev. for MCCP21: 2.89

Thrilled by these statistics!! The MCC14 survey had nearly triple the sample size (862) as this combined survey, but still ended up closer to actual counts. Real life proof of what they tell you in stats classes! A representative sample is the best kind of sample to have. Something I did not consider when using the survey for MCC14 is its source, a blog on Tumblr that talks heavily about Technoblade and Philza, which obviously biased the audience who took it towards the Pink Parrots (Philza, Fundy, Wilbur, JackManifold). Not a surprise we did better this time but really neat to see logic in action! lol

Another interesting thing about the survey: Reddit and Tumblr do vary a little in taste. It's easier to just show you:

What's missing? I chose not to calculate average/median viewership for the creators involved due to the large gap in data. It wouldn't be correct most likely.

So, how did you do this and how did you mess it up?

(I, the writer of this post, mostly do the analysis part of this project, not the programming. Apologies if any programmers are reading this and it doesn't make sense. :[ )

Our initial plan was do do just what we did to collect the MCC14 data but for YouTube instead of Twtich. (For MCC14 we used a Python program to request the viewership data directly from Twitch using their API.) This was much easier said than done. Unlike the Twitch API, which allows you to get stream information very easily just using a streamer's name, YouTube API doesn't have a "front door" way of getting this stuff. So, we went in the "back door."

First thing we had to do was manually collect the user ID for each participant. The next step is where the first error occurred: we needed to get our program to recognize the user ID as a user ID, which was done by writing a rule. This was stuff like how long the IDs were and what symbols were included in the IDs. We failed to include a symbol that was present in five of the participant's user IDs, so the program didn't recognize them as IDs and didn't run them through the part of the program which found the stream ID and collected viewer numbers. This is why that data was missing for SMajor/Noxcrew, ItsFunneh, Squaishey, ASFJerome, and Mefs in the first 30 minutes.

Another big way in which the YouTube API differs from the Twitch API is that YouTube has a quota system. Every action you can take with the API has a certain number of points connected to it, and you're only given so many points to spend a day per application. We thought we were only making one call to get viewer data for every streamer, but instead we were making a separate call for each streamer. That destroyed our quota pretty quick, resulting in the 45 minute gap in data collection. This problem was solved by moving our code into another application which granted us more quota.

This is an important lesson in testing your programs thoroughly before use!

On the bright side, the YouTube API is much more active than the Twitch API, which would update streamer numbers seemingly at random and not all at once. The YouTube API updated numbers roughly every 15 seconds and updated for all streamers, not just a few. That's why our graphs are higher resolution this time!

Here is the raw numbers: Click me!

Let's talk about next time

SO. Obviously this time around was not super ideal, which is partially on us for not testing more. (At least this was not the only scuffed thing about MCCP21. We were just being on brand, if you think about it.) However! Good news! The quota won't be a problem next time as MCC15 won't be Youtube exclusive.   We have already fixed the YouTube program we used this time around and have begun to merge the two. We might even be able to collect YouTube subscribers and Twitch followers by next time but we're focusing on making sure we get all the data next time.

Thank you all so much for reading! Again, any and all critique and questions are welcome! :]

[birlcholtz]

Okay, I'll bite. How and why did you learn to code?

HI LIN thanks for biting this is a story that tells you quite a lot about me as a person

so some background: my parents are both in compsci. they're the late 80s, early 90s silicon valley crowd, they've both had their fair share of established companies and startup-hopping, and my brother and i grew up here

my brother is about 5 years older than me and took to coding like a fish to water (like a duck to water??) which is to say he started programming on scratch at the tender age of.... i don't even know, honestly, maybe 9? too young for me to really remember, and he's been a compsci prodigy ever since

but then. then there was me.

now i do love scratch. when i was little i always copied my brother (not in like a cute way, in a 'if he can do that i can do it too' mindset that meant my third grade teacher REALLY struggled to find book recommendations for me that i hadn't already read. since my brother was above his grade's reading level, and i would read whatever my brother read. yeah that's the kind of kid i was/am)

so naturally i did what he did. i programmed on scratch, i did advanced math courses, i was in CHESS CLUB (i am so bad at chess by the way. i am not good at it. let's establish that. i think i beat my dad once and i genuinely don't know if he let me win or not. i never beat my brother so in that respect i failed. but i'm better than my mom so there's that)

HOWEVER. around fourth or fifth grade i was like hey. maybe i want to like... forge my own identity. and not just turn my life into 'do whatever elder brother does BUT BETTER.'

and thus began my campaign to NEVER DO ANY CODING EVER FOR THE REST OF MY LIFE AND WHILE I'M AT IT FUCK MATH

this gets long so there’s more under the cut sjflsghf

there are two problems with this. the first problem is my inherent pride and the fact that, despite my best efforts, i am actually decent at math and too proud to intentionally fuck it up. so i wound up in honors math. that made part 2 of my independence campaign a little difficult.

the second problem is that my parents were just as determined for me to learn to code as i was to avoid anything to do with coding for the rest of my life

(the third problem was actually a serious problem for this goal. and that was that in seventh grade, when i had a required compsci class where we learned basic, i found myself... enjoying it. HORROR OF HORRORS.)

so i was quite vocal about my anti-math stance and my determination to explore other avenues of life, to which my parents responded by listening with bat-ears whenever i talked about my compsci class and/or my love of spreadsheets so that they could jump on it and say 'YOU KNOW, COMPUTER PROGRAMMING IS JUST LIKE THAT, I THINK YOU WOULD REALLY ENJOY IT' whenever i said something remotely applicable

and to which i responded, of course, by plunging ever deeper into performing arts because fuck compsci, except when it's basic, because then i understand everything because of messing around w scratch when i was little and it's easy and i'm ahead of the rest of the class and can stare into space while the rest of them struggle with closing their parentheses (which is not to say i never messed up my parentheses. i totally did)

now, my brother, because he's a nerd, went to compsci summer camps where you'd spend a week or two learning some program or language. he did things like java and c++ and then would come home and use this knowledge for robotics club. like i said. nerd.

but my parents sensed a golden opportunity. namely, 'if we can get birl to go to these camps, she will actually learn programming things (not just being ahead of the class and spacing out in basic), and we'll probably get her to agree since it's only a week and she can do cost benefit analysis'

and, because i CAN do cost benefit analysis, i agreed to that deal. i'd go to a few of these camps, and then we'd agree that i was done with my parentally mandated computer science requirement. i learned some 3-d modeling, i learned to use unity (which involved some c+ as well), and i learned some java, and all was well. the camps were like 5 days long. we mostly worked on self-directed projects so i could do whatever the hell i wanted (and i made some pretty cool maze games if i do say so myself-- one of them in unity and one of them as a text-based game in java)

and.... horror of horrors....... i didn't hate it.

(of course i didn't want to go BACK any more than i had to but i also didn't hate every moment of those weeks)

so we were out of the woods right?

except no. we weren't.

because here's the thing. my high school ALSO had a computer science requirement. we had to take at least a semester. there were 3 levels offered: AP compsci, normal compsci, and then easy compsci (not its actual name) for the people who did not give a single shit

obviously i wanted to take the last one. my parents really wanted me to take AP but were willing to settle for normal. you will notice there was no overlap

i wrangled my way out of taking AP because that was a year-long course and i didn't have space in my schedule (my parents are wonderful in the sense that they didn't want to infringe on my actual interests to force me to do compsci which meant i had LEVERAGE)

but we literally wound up discussing it with the dean of students who was like 'well if you're capable of AP and just not taking it for schedule reasons then easy compsci would probably be boring for you!' which was an unhelpful take, thanks EVAN

but i did get my way by virtue of volunteering with a progressive tech organization in lieu of taking regular compsci, so i took easy compsci (in which i used scratch again, yay nostalgia, and also briefly flirted with html) and also wound up learning to use squarespace which is criminally easy but you can make it look like you're an expert

and all this while i was getting better and better with spreadsheets due to my own individual love for spreadsheets that near as i can tell, nobody in my family shares (my dad does have a lot of spreadsheets but his aren't as detailed as mine and he doesn't include data validation so HA)

all of which (plus my ap calc and stats classes) combines to mean that while i would not be able to just sit down and write you some code, if you give me access to stack overflow and tell me what language it's supposed to be in i can probably figure it out. especially now that i've become familiar with python by accident (well, more by my desire to write fic)

and because now i'm stuck in a rut, my current internship is with another civic tech company and that's probably what i'll wind up doing next summer as well. i don't actually work on software but i do comms which means i need to be able to have conversations with the engineers so i've been learning on the job. i know so much help

SO. with regards to my fic, my parents would both be thrilled because i taught myself some of a new programming language (python) and disappointed because i taught myself some of a new programming language with just stack overflow and some time and all i'm using it for is fic.

but near as i can tell we finished that battle long ago. it was a resounding victory for birl and i continue to expand my technical talents into areas like photo/video editing and CRM tools.

thank you very much *bows*