#Scrape Tweets data from Twitter

[iwebdatascrape]

Twitter Data Scraping Services -Twitter Data Collection Services

Scrape data like profile handle, followers count, etc., using our Twitter data scraping services. Our Twitter data collection services are functional across the USA, UK, etc.

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[thoughtlessarse]

Far-right populists are significantly more likely to spread fake news on social media than politicians from mainstream or far-left parties, according to a study which argues that amplifying misinformation is now part and parcel of radical right strategy. “Radical right populists are using misinformation as a tool to destabilise democracies and gain political advantage,” said Petter Törnberg of the University of Amsterdam, a co-author of the study with Juliana Chueri of the Dutch capital’s Free University. “The findings underscore the urgent need for policymakers, researchers, and the public to understand and address the intertwined dynamics of misinformation and radical right populism,” Törnberg added. The research draws on every tweet posted between 2017 and 2022 by every member of parliament with a Twitter (now X) account in 26 countries: 17 EU members including Austria, France, Germany, the Netherlands and Sweden, but also the UK, US and Australia. It then compared that dataset – 32m tweets from 8,198 MPs – with international political science databases containing detailed information on the parties involved, such as their position on the left-right spectrum and their degree of populism. Finally, the researchers scraped factchecking and fake news-tracking services to build a dataset of 646,058 URLs, each with an associated “factuality rating” based on the reliability of its source – and compared that data with the 18m URLs shared by the MPs. By crunching all the different datasets together, the researchers were able to create what they described as an aggregate “factuality score” for each politician and each party, based on the links that MPs had shared on Twitter. The data showed conclusively that far-right populism was “the strongest determinant for the propensity to spread misinformation”, they concluded, with MPs from centre-right, centre-left and far-left populist parties “not linked” to the practice.

continue reading

It's the only way they can win, i.e. by telling lies.

[mariacallous]

While the finer points of running a social media business can be debated, one basic truth is that they all run on attention. Tech leaders are incentivized to grow their user bases so there are more people looking at more ads for more time. It’s just good business.

As the owner of Twitter, Elon Musk presumably shared that goal. But he claimed he hadn’t bought Twitter to make money. This freed him up to focus on other passions: stopping rival tech companies from scraping Twit­ter’s data without permission—even if it meant losing eyeballs on ads.

Data-scraping was a known problem at Twitter. “Scraping was the open secret of Twitter data access. We knew about it. It was fine,” Yoel Roth wrote on the Twitter ­alternative Bluesky. AI firms in particular were no­torious for gobbling up huge swaths of text to train large language models. Now that those firms were worth a lot of money, the situation was far from fine, in Musk’s opinion.

In November 2022, OpenAI debuted ChatGPT, a chatbot that could generate convincingly human text. By January 2023, the app had over 100 million users, making it the fastest ­growing consumer app of all time. Three months later, OpenAI secured another round of funding that closed at an astounding valuation of $29 billion, more than Twitter was worth, by Musk’s estimation.

OpenAI was a sore subject for Musk, who’d been one of the original founders and a major donor before stepping down in 2018 over disagree­ments with the other founders. After ChatGPT launched, Musk made no secret of the fact that he disagreed with the guardrails that OpenAI put on the chatbot to stop it from relaying dangerous or insensitive infor­mation. “The danger of training AI to be woke—in other words, lie—is deadly,” Musk said on December 16, 2022. He was toying with starting a competitor.

Near the end of June 2023, Musk launched a two-part offensive to stop data scrapers, first directing Twitter employees to temporarily block “logged out view.” The change would mean that only people with Twitter accounts could view tweets.

“Logged out view” had a complicated history at Twitter. It was rumored to have played a part in the Arab Spring, allowing dissidents to view tweets without having to create a Twitter account and risk compromising their anonymity. But it was also an easy access point for people who wanted to scrape Twitter data.

Once Twitter made the change, Google was temporarily blocked from crawling Twitter and serving up relevant tweets in search results—a move that could negatively impact Twitter’s traffic. “We’re aware that our ability to crawl Twitter.com has been limited, affecting our ability to display tweets and pages from the site in search results,” Google spokesperson Lara Levin told The Verge. “Websites have control over whether crawlers can access their content.” As engineers discussed possible workarounds on Slack, one wrote: “Surely this was expected when that decision was made?”

Then engineers detected an “explosion of logged in requests,” according to internal Slack messages, indicating that data scrapers had simply logged in to Twitter to continue scraping. Musk ordered the change to be reversed.

On July 1, 2023, Musk launched part two of the offensive. Suddenly, if a user scrolled for just a few minutes, an error message popped up. “Sorry, you are rate limited,” the message read. “Please wait a few moments then try again.”

Rate limiting is a strategy that tech companies use to constrain net­work traffic by putting a cap on the number of times a user can perform a specific action within a given time frame (a mouthful, I know). It’s often used to stop bad actors from trying to hack into people’s accounts. If a user tries an incorrect password too many times, they see an error mes­sage and are told to come back later. The cost of doing this to someone who has forgotten their password is low (most people stay logged in), while the benefit to users is very high (it prevents many people’s accounts from getting compromised).

Except, that wasn’t what Musk had done. The rate limit that he ordered Twitter to roll out on July 1 was an API limit, meaning Twitter had capped the number of times users could refresh Twitter to look for new tweets and see ads. Rather than constrain users from performing a specific ac­tion, Twitter had limited all user actions. “I realize these are draconian rules,” a Twitter engineer wrote on Slack. “They are temporary. We will reevaluate the situation tomorrow.”

At first, Blue subscribers could see 6,000 posts a day, while nonsubscribers could see 600 (enough for just a few minutes of scroll­ing), and new nonsubscriber accounts could see just 300. As people started hitting the limits, #TwitterDown started trending on, well, Twitter. “This sucks dude you gotta 10X each of these numbers,” wrote user @tszzl.

The impact quickly became obvious. Companies that used Twitter di­rect messages as a customer service tool were unable to communicate with clients. Major creators were blocked from promoting tweets, putting Musk’s wish to stop data scrapers at odds with his initiative to make Twit­ter more creator­ friendly. And Twitter’s own trust and safety team was suddenly stopped from seeing violative tweets.

Engineers posted frantic updates in Slack. “FYI some large creators com­plaining because rate limit affecting paid subscription posts,” one said.

Christopher Stanley, the head of information security, wrote with dis­may that rate limits could apply to people refreshing the app to get news about a mass shooting or a major weather event. “The idea here is to stop scrapers, not prevent people from obtaining safety information,” he wrote. Twitter soon raised the limits to 10,000 (for Blue subscribers), 1,000 (for nonsubscribers), and 500 (for new nonsubscrib­ers). Now, 13 percent of all unverified users were hitting the rate limit.

Users were outraged. If Musk wanted to stop scrapers, surely there were better ways than just cutting off access to the service for everyone on Twitter.

“Musk has destroyed Twitter’s value & worth,” wrote attorney Mark S. Zaid. “Hubris + no pushback—customer empathy—data = a great way to light billions on fire,” wrote former Twitter product manager Esther Crawford, her loyalties finally reversed.

Musk retweeted a joke from a parody account: “The reason I set a ‘View Limit’ is because we are all Twitter addicts and need to go outside.”

Aside from Musk, the one person who seemed genuinely excited about the changes was Evan Jones, a product manager on Twitter Blue. For months, he’d been sending executives updates regarding the anemic sign­up rates. Now, Blue subscriptions were skyrocketing. In May, Twitter had 535,000 Blue subscribers. At $8 per month, this was about $4.2 million a month in subscription revenue. By early July, there were 829,391 subscribers—a jump of about $2.4 million in revenue, not accounting for App Store fees.

“Blue signups still cookin,” he wrote on Slack above a screenshot of the sign­up dashboard.

Jones’s team capitalized on the moment, rolling out a prompt to upsell users who’d hit the rate limit and encouraging them to subscribe to Twit­ter Blue. In July, this prompt drove 1.7 percent of the Blue subscriptions from accounts that were more than 30 days old and 17 percent of the Blue subscriptions from accounts that were less than 30 days old.

Twitter CEO Linda Yaccarino was notably absent from the conversation until July 4, when she shared a Twitter blog post addressing the rate limiting fiasco, perhaps deliberately burying the news on a national holiday.

“To ensure the authenticity of our user base we must take extreme measures to remove spam and bots from our platform,” it read. “That’s why we temporarily limited usage so we could detect and eliminate bots and other bad actors that are harming the platform. Any advance notice on these actions would have allowed bad actors to alter their behavior to evade detection.” The company also claimed the “effects on advertising have been minimal.”

If Yaccarino’s role was to cover for Musk’s antics, she was doing an ex­cellent job. Twitter rolled back the limits shortly after her announcement. On July 12, Musk debuted a generative AI company called xAI, which he promised would develop a language model that wouldn’t be politically correct. “I think our AI can give answers that people may find controver­sial even though they are actually true,” he said on Twitter Spaces.

Unlike the rival AI firms he was trying to block, Musk said xAI would likely train on Twitter’s data.

“The goal of xAI is to understand the true nature of the universe,” the company said grandly in its mission statement, echoing Musk’s first, di­sastrous town hall at Twitter. “We will share more information over the next couple of weeks and months.”

In November 2023, xAI launched a chatbot called Grok that lacked the guardrails of tools like ChatGPT. Musk hyped the release by posting a screenshot of the chatbot giving him a recipe for cocaine. The company didn’t appear close to understanding the nature of the universe, but per­ haps that’s coming.

Excerpt adapted from Extremely Hardcore: Inside Elon Musk’s Twitter by Zoë Schiffer. Published by arrangement with Portfolio Books, a division of Penguin Random House LLC. Copyright © 2024 by Zoë Schiffer.

[hell-of-blazing-fires]

Currently fully abandoning twitter because it's already a shithole, it's getting worse, about to start scraping all your data for ai training and it's a soon to be state propaganda site. So I've started tracing accounts to other platforms.

Went through my follows and now going through my bookmarks and it is an absolutely miserable process. But here's some things that have made it slightly more bearable.

I used it as a lurker mostly as a means to see art so that's where these tips are coming from.

You can get an archive of your twitter data.

Settings -> Your Account -> Download an archive of your data.

It takes a while so check the email your account is linked to. It has your tweets, retweets, DMs, etc. I used it to get my likes which is given to you in a big ass list of links. Also be aware that it does NOT archive your bookmarks.

Sky Follower Bridge

Finds the Bluesky accounts of your follows, followers or list members from their twitter name or links in their bio. It's far from perfect as their Bluesky name has to match their handle or display name perfectly or it doesn't work. But it will hopefully cut down a fair bit of work in finding people.

If an artist has a page there, it will have a list of links to their profiles across the internet. It's a lot more useful than you'd think it'd be because even a ton of small artists have pages. Though they are only as complete as the people who create and edits the pages makes them so it can be hit or miss.

Danbooru

I'd suggest searching with (artist name) + danbooru as the in-site search is janky with aliases.

Most Eastern artists, especially Japanese ones, use Pixiv. It's an annoying site to use because it locks basic features behind paywalls (Like sorting by most popular and the fucking ability to blacklist tags.) But a large majority of them can be found there.

Danbooru has a lot of porn on it (without filters by default) in addition to sfw drawings. Just be warned.

Pixiv

If you know a way to archive bookmarks definitely share that because all the methods I saw are broken and I'm pretty sure the only way to archive it is by doing it manually which is awful. Also these are just the methods I used for myself, please feel free to share others.

[mikesmatcha]

Moving Forward (on Twitter and other social media platforms)

MikesMatcha started out on Twitter last June 2022, and it has gained almost 500 followers since then. I understand that's a very slow growth, but it's still something impressive with just a year of that account. But from now on I'll prioritize posting here first after glazing my artwork, as Twitter is now becoming an AI data scraping site.

I'll still post on Threads and Instagram too, but for Twitter it will take a lot of glazing and protecting my art against AI theft.

Context on slow growth: I ship an Attack on Titan rarepair so I grew slow, and there's a particular group of shippers who spout bullshit against that rarepair to their 2K - 6K Twitter followers as well as some (not all, some) their big name artist friends. I also ship the archrival ship too so they're truly something.

After Elon Musk did a lot of things–lately the following, unless you pay him money regularly to use the site:

rate limiting viewing of tweets

limiting DMs

rebranding to the bullshit called "X", his not so obvious favorite letter in the alphabet

And lately, with X Twitter announcing they'll be data scraping from their site, it's caused many of my moots and favorite artists to leave the app, including some of my fandom besties–voluntarily, or involuntarily (one of them is Indonesian and rebranding to "X" has gotten Twitter in trouble with Indonesian law).

So moving forward, you'll see more of my fan art here.

[crispytoastyt]

Twitter Is Dead. Now What?

Well, it happened. Elon Musk killed the platform by announcing how many tweets you can read per day in an attempt to force you to subscribe to Twitter Blue. This really proves that Elon Musk is not a really good engineer and takes advantage of the platform to add toxic features that force them to cough up the money. The worst part is that he lied to the user base because he was data-scraping.

With Twitter dead, it seems like many people are eyeing possible alternatives. From what I can see, Spoutible and BlueSky are the two recommended platforms. However, they are not perfect but doable.

BlueSky is currently in closed beta and only those who have the invite from either the devs themselves or friends can sign up. While it works exactly like Twitter, the one thing I notice about it is that hashtags are not working. Maybe they need to implement it since hashtags are trendy tools to work with.

Spoutible can also work as an alternative, even though the majority of users are politically based and it is hard to find people with common interests. I want to connect with artists over there, but I do not know who.

Now, let us address the mammoth in the room if you know what I mean. I know that there is already Mastodon but it has a problem with an identity crisis. I would consider it but... nah.

So yeah. Twitter is dead. It is time to move on. It is beyond saving at this point. The FCC will most likely find Elon Musk accountable for his actions and pretty soon he may be facing jail time.

[quillirio]

I’m proud to say I contributed to the data scraping on twitter that made elon so pissy 🎉 fuck you bitch 🎉🎉🎉

But huh, I wonder why there’d be extreme amounts of data scraping… maybe to save tweets from being deleted by elon..? it’s almost like this is a direct result of his poor management.

[thoughtportal]

lon Musk will use Twitter data to build and train an AI to counter ChatGPT.

He mentioned the plan during a Friday Twitter Spaces discussion that shared more details about his plans for xAI, his newest startup. 

"Every organization doing AI, large and small, has used Twitter’s data for training, basically in all cases illegally,” he said(Opens in a new window), later adding: "We had multiple entities scraping every tweet ever made, and trying to do so in a span of days."

Twitter recently imposed rate limits to prevent companies from scraping data from the platform. However, Musk plans on opening up the tweet access for xAI. “We will use the public tweets —obviously not anything private— for training as well just like everyone else has,” he said. 

Twitter’s data is valuable for AI companies because the user-generated content is fresh and covers a variety of topics using text that could help chatbots better mimic human speech.    

It’s also possible the data could help xAI’s own forthcoming chatbot produce more accurate responses, thanks to Twitter’s Community Notes feature, which lets users flag misleading tweets by providing additional context. However, training an AI with tweets could spark lawsuits and regulatory issues. Earlier this week, the FTC told OpenAI it's investigating the company for potentially violating user privacy by collecting data from across the internet to train ChatGPT. 

Musk was vague on what xAI is creating. But he said the startup’s goal is to develop a “useful AI” for both consumers and businesses. Meanwhile, the long-term vision is to develop an AGI or artificial intelligence that can solve a wide-range of tasks, like a human can.  

“We are definitely the competition,” he said, referencing OpenAI and Google, which released its Bard chatbot earlier this year. “You don’t want to have a unipolar world, where just one company kind of dominates in AI.” 

However, he also emphasized his forthcoming AI will “pursue the truth.” Although rival chatbots have been programmed with content moderation in mind, Musk previously criticized ChatGPT as a propaganda machine focused on political correctness. During the Twitter Spaces discussion, Musk reiterated his concerns. 

“At xAI we have to let the AI say what it really believes is true, and not be deceptive or politically correct,” he said. Musk then compared the danger to the AI computer that goes insane in the sci-fi classic 2001: A Space Odyssey and kills the crew. “Where did things go wrong in Space Odyssey? Basically, when they told HAL 9000 to lie.”

Musk has recruited almost a dozen engineers and researchers from Google, Microsoft, and OpenAI to help him run the San Francisco-based xAI. The startup hopes to share more information about its “first release” in the coming weeks.

[starweed]

[id;

supernatural meme with castiel saying, “i love you” and dean replying, “twitter has begun rationing views”

below is a screenshot of a tweet from elon musk that says, “to address levels of data scraping [and] system manipulation, we’ve applied temporary limits:

verified accounts are limited to reading 6,000 [posts per day]

non-verified accounts to 600 posts/day

new unverified accounts to 300/day

the third image is a screenshot from @/photonsmight which says, “the worst part of all of this is, why i opened tumblr and they all over there laughing at us”

end id]

[scrapegg]

How to Use a Twitter Scraper Tool Easily

Why Twitter Scraping Changed My Social Media Game

Let me share a quick story. Last year, I was managing social media for a small tech startup, and we were struggling to create content that resonated with our audience. I was spending 4–5 hours daily just browsing Twitter, taking screenshots, and manually tracking competitor posts. It was exhausting and inefficient.

That’s when I discovered the world of Twitter scraping tool, and honestly, it was a game-changer. Within weeks, I was able to analyze thousands of tweets, identify trending topics in our niche, and create data-driven content strategies that increased our engagement by 300%.

What Exactly is a Twitter Scraper Tool?

Simply put, a Twitter scraping tool is software that automatically extracts data from Twitter (now X) without you having to manually browse and copy information. Think of it as your personal digital assistant that works 24/7, collecting tweets, user information, hashtags, and engagement metrics while you focus on more strategic tasks.

These tools can help you:

Monitor brand mentions and sentiment

Track competitor activities

Identify trending topics and hashtags

Analyze audience behavior patterns

Generate leads and find potential customers

Finding the Best Twitter Scraper Online: My Personal Experience

After testing dozens of different platforms over the years, I’ve learned that the best twitter scraper online isn’t necessarily the most expensive one. Here’s what I look for when evaluating scraping tools:

Key Features That Actually Matter

1. User-Friendly Interface The first time I used a complex scraping tool, I felt like I needed a computer science degree just to set up a basic search. Now, I only recommend tools that my grandmother could use (and she’s not exactly tech-savvy!).

2. Real-Time Data Collection In the fast-paced world of Twitter, yesterday’s data might as well be from the stone age. The best tools provide real-time scraping capabilities.

3. Export Options Being able to export data in various formats (CSV, Excel, JSON) is crucial for analysis and reporting. I can’t count how many times I’ve needed to quickly create a presentation for stakeholders.

4. Rate Limit Compliance This is huge. Tools that respect Twitter’s API limits prevent your account from getting suspended. Trust me, I learned this the hard way.

Step-by-Step Guide: Using an X Tweet Scraper Tool

Based on my experience, here’s the easiest way to get started with any x tweet scraper tool:

Step 1: Define Your Scraping Goals

Before diving into any tool, ask yourself:

What specific data do I need?

How will I use this information?

What’s my budget and time commitment?

I always start by writing down exactly what I want to achieve. For example, “I want to find 100 tweets about sustainable fashion from the past week to understand current trends.”

Step 2: Choose Your Scraping Parameters

Most tweet scraper online tools allow you to filter by:

Keywords and hashtags

Date ranges

User accounts

Geographic location

Language

Engagement levels (likes, retweets, replies)

Step 3: Set Up Your First Scraping Project

Here’s my tried-and-true process:

Start Small: Begin with a narrow search (maybe 50–100 tweets) to test the tool

Test Different Keywords: Use variations of your target terms

Check Data Quality: Always review the first batch of results manually

Scale Gradually: Once you’re confident, increase your scraping volume

My Final Thoughts

Using a twitter scraper tool effectively isn’t just about having the right software — it’s about understanding your goals, respecting platform rules, and continuously refining your approach. The tools I use today are vastly different from what I started with, and that’s okay. The key is to keep learning and adapting.

Whether you’re a small business owner trying to understand your audience, a researcher analyzing social trends, or a marketer looking to stay ahead of the competition, the right scraping approach can provide invaluable insights.

[tagx01]

How to Use Twitter Scraping for Investment & Stock Market Sentiment Analysis

In today’s fast-paced digital economy, investment decisions are no longer driven solely by financial news channels or quarterly reports. A single tweet from an influential figure or a trending hashtag can sway investor sentiment and send stocks soaring or crashing within minutes. With over 500 million tweets posted daily, Twitter scraping has emerged as a powerful technique for investors and analysts seeking real-time, unfiltered insights into public market sentiment.

Whether you're a retail investor, a financial analyst, or a hedge fund researcher, scraping data from Twitter offers a unique edge, giving you the pulse of the market before traditional news sources catch on.

 In this blog, we’ll explore the methodology, tools, benefits, challenges, and ethical considerations of Twitter scraping for stock market and investment sentiment analysis.

Why Twitter Matters in Stock Market Analysis

Twitter is a live stream of human emotion, speculation, and reaction. It’s where financial news breaks, where influencers share insights, and where trends start—often before mainstream media picks them up.

For example:

Elon Musk tweets about a cryptocurrency, prices spike instantly.

A viral thread highlights a supply chain issue at a major company, prompting investors to begin selling.

These moments are invaluable if identified in time. Twitter enables crowd-sourced sentiment, which can be harnessed through scraping and turned into actionable intelligence.

What is Twitter Scraping?

Twitter scraping refers to the automated extraction of public tweets and metadata such as hashtags, mentions, timestamps, and user information for analysis purposes. This process does not rely solely on Twitter’s API and instead uses scripts or scraping tools to gather large datasets beyond API limitations.

When done ethically and in compliance with Twitter’s terms, scraping allows analysts to:

Collect real-time mentions of stock tickers (e.g., $AAPL, $AMZN)

Analyze public opinion on corporate events

Track emerging trends before they reflect in stock prices

This scraped data becomes the foundation for sentiment analysis, pattern detection, and market forecasting.

Applications of Twitter Scraping in Investment

1. Sentiment Analysis for Individual Stocks

By collecting tweets referencing specific stock tickers (like $TSLA), you can determine the public mood—bullish, bearish, or neutral. This sentiment can be quantified using NLP (Natural Language Processing) tools. A surge in positive sentiment may precede a stock price rise, offering an opportunity to buy in early.

2. Trend Detection Across Sectors

Instead of focusing on a single company, investors can analyze tweets related to entire sectors. By tracking hashtags such as TechStocks, EVs, or #HealthcareInvesting, you can discover sector trends and consumer sentiment shifts that might influence sector-wide ETFs or multiple company stocks.

3. Earnings Season Intelligence

Earnings reports often generate a flood of public response. Twitter scraping allows you to analyze these reactions in real time. Public dissatisfaction or enthusiasm post-earnings can help determine whether the market will respond positively or negatively.

4. Crisis Monitoring and Early Warnings

Public outrage or controversy spreads quickly on social media. Detecting early signs of corporate crises—like lawsuits, data breaches, or executive misconduct—via spikes in tweet volume gives you a chance to take proactive investment actions.

How to Use Twitter Scraping for Stock Market Sentiment

Step 1: Define Your Objectives

Start by clarifying what insights you want:

Are you monitoring a specific stock or a sector?

Do you want historical or real-time data?

Are you tracking influencer impact or general public sentiment?Having a clear focus ensures efficient scraping and more accurate analysis.

Step 2: Choose Your Tools

Several tools can help you automate Twitter data collection:

SNScrape: A command-line tool that doesn't need API keys and can extract tweets based on keywords, hashtags, usernames, or dates.

TagX, a leader in custom data services, offers turnkey Twitter scraping solutions tailored for investment analysis. Their expertise includes real-time scraping infrastructure, scalable pipelines, and domain-specific sentiment models. TagX ensures not only access to large datasets but also the accuracy and cleanliness needed for reliable decision-making.

Tweepy: A Python library that uses Twitter’s API for structured access. Best for developers comfortable with API constraints.

BeautifulSoup + Selenium: Used for scraping dynamic Twitter pages but requires more manual configuration.

Step 3: Clean and Filter Your Data

Raw Twitter data includes a lot of noise. Cleaning involves:

Removing irrelevant tweets or spam

Filtering by language, keywords, cashtags, or geolocation

Excluding bot-generated content

The cleaner your dataset, the more trustworthy your sentiment results.

Step 5: Visualize Your Findings

Use visualization tools to make insights actionable:

Matplotlib or Seaborn for Python-based visuals

Tableau or Power BI for enterprise-level dashboards

Plotly for interactive charts

Graph tweet volume, sentiment trends, and stock price movement to detect correlations and forecast outcomes.

Benefits of Twitter Scraping in Investment Strategy

Early Access to Market Sentiment

Gain insights before they hit mainstream financial outlets. Twitter provides a window into public opinion and emerging discussions ahead of official news.

Behavioral Insights into Retail Investors

Track emotional reactions, memes, or viral trends driven by non-institutional traders—particularly valuable during speculative rallies.

High Scalability with Cost Efficiency

Scraping offers an affordable way to gather massive datasets compared to paid APIs or market research platforms, making it ideal for startups and analysts.

Custom Analytics Aligned with Goals

Scraping enables you to design custom pipelines that fit your investment strategy—whether for swing trading, long-term value investing, or sector monitoring.

Why TagX is the Right Partner for Twitter Sentiment Solutions

TagX is a leading provider of AI-powered data services, helping financial analysts, trading platforms, and fintech companies gather structured social media insights at scale. From setting up compliant Twitter scraping pipelines to integrating sentiment models, TagX offers:

Scalable social scraping infrastructure

Custom keyword filtering and NLP models

Financial sentiment scoring tuned for accuracy

End-to-end data integration for dashboards or ML pipelines

Whether you need raw data feeds or fully visualized insights, TagX can help you extract real value from real-time Twitter conversations

Final Thoughts

In a world where tweets can trigger stock surges or crashes, understanding social sentiment isn’t just useful—it’s essential. Twitter scraping offers investors a competitive advantage by converting unstructured chatter into structured, insightful signals.

With the right tools and partners like TagX, you can automate this intelligence gathering and make smarter, faster investment decisions that reflect the market’s real-time pulse.

[actowizsolutions0]

News Extract: Unlocking the Power of Media Data Collection

In today's fast-paced digital world, staying updated with the latest news is crucial. Whether you're a journalist, researcher, or business owner, having access to real-time media data can give you an edge. This is where news extract solutions come into play, enabling efficient web scraping of news sources for insightful analysis.

Why Extracting News Data Matters

News scraping allows businesses and individuals to automate the collection of news articles, headlines, and updates from multiple sources. This information is essential for:

Market Research: Understanding trends and shifts in the industry.

Competitor Analysis: Monitoring competitors’ media presence.

Brand Reputation Management: Keeping track of mentions across news sites.

Sentiment Analysis: Analyzing public opinion on key topics.

By leveraging news extract techniques, businesses can access and process large volumes of news data in real-time.

How News Scraping Works

Web scraping involves using automated tools to gather and structure information from online sources. A reliable news extraction service ensures data accuracy and freshness by:

Extracting news articles, titles, and timestamps.

Categorizing content based on topics, keywords, and sentiment.

Providing real-time or scheduled updates for seamless integration into reports.

The Best Tools for News Extracting

Various scraping solutions can help extract news efficiently, including custom-built scrapers and APIs. For instance, businesses looking for tailored solutions can benefit from web scraping services India to fetch region-specific media data.

Expanding Your Data Collection Horizons

Beyond news extraction, companies often need data from other platforms. Here are some additional scraping solutions:

Python scraping Twitter: Extract real-time tweets based on location and keywords.

Amazon reviews scraping: Gather customer feedback for product insights.

Flipkart scraper: Automate data collection from India's leading eCommerce platform.

Conclusion

Staying ahead in today’s digital landscape requires timely access to media data. A robust news extract solution helps businesses and researchers make data-driven decisions effortlessly. If you're looking for reliable news scraping services, explore Actowiz Solutions for customized web scraping solutions that fit your needs.

[gts37889]

A Comprehensive Handbook on Datasets for Machine Learning Initiatives

Introduction:

Datasets in Machine Learning is fundamentally dependent on data. Whether you are a novice delving into predictive modeling or a seasoned expert developing deep learning architectures, the selection of an appropriate dataset is vital for achieving success. This detailed guide will examine the various categories of datasets, sources for obtaining them, and criteria for selecting the most suitable ones for your machine learning endeavors.

The Importance of Datasets in Machine Learning

A dataset serves as the foundation for any machine learning model. High-quality and well-organized datasets enable models to identify significant patterns, whereas subpar data can result in inaccurate and unreliable outcomes. Datasets impact several aspects, including:

 Model accuracy and efficiency

 Feature selection and engineering

 Generalizability of models

 Training duration and computational requirements

Selecting the appropriate dataset is as critical as choosing the right algorithm. Let us now investigate the different types of datasets and their respective applications.

Categories of Machine Learning Datasets

Machine learning datasets are available in various formats and serve multiple purposes. The primary categories include:

1. Structured vs. Unstructured Datasets

Structured data: Arranged in a tabular format consisting of rows and columns (e.g., Excel, CSV files, relational databases).

Unstructured data: Comprises images, videos, audio files, and text that necessitate preprocessing prior to being utilized in machine learning models.

2. Supervised vs. Unsupervised Datasets

Supervised datasets consist of labeled information, where input-output pairs are clearly defined, and are typically employed in tasks related to classification and regression.

Unsupervised datasets, on the other hand, contain unlabeled information, allowing the model to independently identify patterns and structures, and are utilized in applications such as clustering and anomaly detection.

3. Time-Series and Sequential Data

These datasets are essential for forecasting and predictive analytics, including applications like stock market predictions, weather forecasting, and data from IoT sensors.

4. Text and NLP Datasets

Text datasets serve various natural language processing functions, including sentiment analysis, the development of chatbots, and translation tasks.

5. Image and Video Datasets

These datasets are integral to computer vision applications, including facial recognition, object detection, and medical imaging.

Having established an understanding of the different types of datasets, we can now proceed to examine potential sources for obtaining them.

Domain-Specific Datasets

Healthcare and Medical Datasets

MIMIC-III – ICU patient data for medical research.

Chest X-ray Dataset  – Used for pneumonia detection.

Finance and Economics Datasets

Yahoo Finance API – Financial market and stock data.

Quandl – Economic, financial, and alternative data.

Natural Language Processing (NLP) Datasets

Common Crawl – Massive web scraping dataset.

Sentiment140  – Labeled tweets for sentiment analysis.

Computer Vision Datasets

ImageNet  – Large-scale image dataset for object detection.

COCO (Common Objects in Context) – Image dataset for segmentation and captioning tasks.

Custom Dataset Generation

When publicly available datasets do not fit your needs, you can:

Web Scraping: Use BeautifulSoup or Scrapy to collect custom data.

APIs: Utilize APIs from Twitter, Reddit, and Google Maps to generate unique datasets.

Synthetic Data: Create simulated datasets using libraries like Faker or Generative Adversarial Networks (GANs).

Selecting an Appropriate Dataset

The choice of an appropriate dataset is influenced by various factors:

Size and Diversity – A dataset that is both large and diverse enhances the model's ability to generalize effectively.

Data Quality – High-quality data that is clean, accurately labeled, and devoid of errors contributes to improved model performance.

Relevance – It is essential to select a dataset that aligns with the specific objectives of your project.

Legal and Ethical Considerations – Ensure adherence to data privacy laws and regulations, such as GDPR and HIPAA.

In Summary

Datasets serve as the cornerstone of any machine learning initiative. Regardless of whether the focus is on natural language processing, computer vision, or financial forecasting, the selection of the right dataset is crucial for the success of your model. Utilize platforms such as GTS.AI to discover high-quality datasets, or consider developing your own through web scraping and APIs.

With the appropriate data in hand, your machine learning project is already significantly closer to achieving success.

[mariacallous]

Soon after Elon Musk took control of Twitter, now called X, the platform faced a massive problem: Advertisers were fleeing. But that, the company alleges, was someone else’s fault. On Thursday that argument went before a federal judge, who seemed skeptical of the company's allegations that a nonprofit’s research tracking hate speech on X had compromised user security, and that the group was responsible for the platform’s loss of advertisers.

The dispute began in July when X filed suit against the Center for Countering Digital Hate, a nonprofit that tracks hate speech on social platforms and had warned that the platform was seeing an increase in hateful content. Musk’s company alleged that CCDH’s reports cost it millions in advertising dollars by driving away business. It also claimed that the nonprofit’s research had violated the platform’s terms of service and endangered users’ security by scraping posts using the login of another nonprofit, the European Climate Foundation.

In response, CCDH filed a motion to dismiss the case, alleging that it was an attempt to silence a critic of X with burdensome litigation using what’s known as a “strategic lawsuit against public participation,” or SLAPP.

On Thursday, lawyers for CCDH and X went before Judge Charles Breyer in the Northern California District Court for a hearing to decide whether X’s case against the nonprofit will be allowed to proceed. The outcome of the case could set a precedent for exactly how far billionaires and tech companies can go to silence their critics. “This is really a SLAPP suit disguised as a contractual suit,” says Alejandra Caraballo, clinical instructor at Harvard Law School's Cyberlaw Clinic.

Unforeseen Harms

X alleges that the CCDH used the European Climate Foundation’s login to a social network listening tool called Brandwatch, which has a license to access X data through the company’s API. In the hearing Thursday, X’s attorneys argued that CCDH’s use of the tool had caused the company to spend time and money investigating the scraping, for which it also needed to be compensated on top of payback for how the nonprofit’s report spooked advertisers.

Judge Breyer pressed X’s attorney, Jonathan Hawk, on that claim, questioning how scraping posts that were publicly available could violate users’ safety or the security of their data. “If [CCDH] had scraped and discarded the information, or scraped that number and never issued a report, or scraped and never told anybody about it. What would be your damages?” Breyer asked X’s legal team.

Breyer also pointed out that it would have been impossible for anyone agreeing to Twitter's terms of service in 2019, as the European Climate Foundation did when it signed up for Brandwatch, years before Musk’s purchase of the platform, to anticipate how its policies would drastically change later. He suggested it would be difficult to hold CCDH responsible for harms it could not have foreseen.

“Twitter had a policy of removing tweets and individuals who engaged in neo-Nazi, white supremacists, misogynists, and spreaders of dangerous conspiracy theories. That was the policy of Twitter when the defendant entered into its terms of service,” Breyer said. “You're telling me at the time they were excluded from the website, it was foreseeable that Twitter would change its policies and allow these people on? And I am trying to figure out in my mind how that's possibly true, because I don't think it is."

Speaking after the hearing, Imran Ahmed, CEO of CCDH, was optimistic about the direction of the judge’s inquiry. “We were particularly surprised by the implication in X Corp.’s argument today that it thinks that CCDH should somehow be on the hook for paying for X Corp. to help neo-Nazis, white supremacists, and misogynists escape scrutiny of their reprehensible posts,” he says. “We can't help but note that X Corp. really had no response to our assertion that Musk changed X's policies to reinstate white supremacists, neo-Nazis, misogynists, and other propagators of hateful and toxic content.”

Breyer did not indicate Thursday when he would rule on whether the case could move forward.

Broken Trust

After taking over Twitter in late 2022, Musk fired much of the company's trust and safety team, which kept hateful and dangerous content as well as disinformation off the platform. He then also offered amnesty to users who had been banned for violating the platform’s policies. CCDH is among a number of organizations and academics who have published evidence showing that X has become a haven for harmful and misleading content under Musk’s watch.

The suit against CCDH was just one of many ways in which platforms have sought to limit transparency in recent years. X now charges $42,000 for access to its API, making analyzing data from the platform financially inaccessible to many researchers and members of civil society. For its part, Meta has wound down CrowdTangle, a tool that allowed researchers and journalists to track the spread of posts, and cut off researchers at New York University who were studying political ads and Covid-19 disinformation.

Both Meta and X filed suit against Bright Data, a third-party data collection service, for scraping their platforms. In January, Meta’s case against Bright Data was dismissed. “The Facebook and Instagram Terms do not bar logged-off scraping of public data; perforce it does not prohibit the sale of such public data,” wrote US federal judge Edward Chen in his verdict. “The Terms cannot bar Bright Data’s logged-off scraping activities.”

Bright Data spokesperson Jennifer Burns calls the platforms’ suits against the company “an effort to build a wall around publicly available data.”

Caraballo, of Harvard Law School, says Elon Musk appears to have decided lawsuits are a good strategy for silencing critics of his social platform. In November, X filed a lawsuit against the watchdog group Media Matters for America, accusing the group of trying to drive advertisers away from the platform by reporting how ads appeared next to neo-Nazi content.

The suit was filed in Texas, where anti-SLAPP laws that can be used to quash frivolous lawsuits do not apply in federal courts, which will make it more difficult for the case to be dismissed, says Caraballo. “I think it's incredibly concerning that this is part of that broader pattern, because these are the mechanisms that hold powerful companies accountable,” she says.

She guesses that while X might be able to move forward with a narrow version of its claim that CCDH breached its terms of service, “most of the claims will get tossed out.”

X did not respond to request for comment by the time of publication.

[d2kvirus]

Dickheads of the Month: December 2024

As it seems that there are people who say or do things that are remarkably dickheaded yet somehow people try to make excuses for them or pretend it never happened, here is a collection of some of the dickheaded actions we saw in the month of December 2024 to make sure that they are never forgotten.  

Murder boner with a flag Israel showed just how committed they were to uphold their ceasefire with Lebanon by violating that ceasefire over 100 times within the first week of said ceasefire. The most moral army in the world, ladies and gentlemen!

Of course it was time for billionaire manchild Elon Musk to have another one of his brilliant ideas, tis time removing timestamps from tweets which effectively makes them useless for academic, journalistic or legal purposes, which appears to be in response to him thirst-tweeting Tiffany Fong an unhealthy amount of times before she told him to fuck right off

...and then billionaire manchild Elon Musk decided he hadn't interfered in enough country's elections, so endorsed AfD ahead of the German elections - and when called out for it invoked horseshoe theory, failing to grasp that when one side is castigating you for supporting literal Nazis and the other side is castigating you for not supporting literal Nazis enough that is not horseshoe theory

...soon followed by billionaire manchild Elon Musk continuing to interfere in German politics by saying that Olaf Scolz should resign as Chancellor after the Magdeburg attack - though for some strange reason seemed to go very, very quiet on that subject when it emerged the perpetrator was an Islamaphobic, pro-Zionist follower of bonehead messiah Tommy Robinson

...so of course billionaire manchild Elon Musk then showed his dedication to FREEZE PEACH by deleting the attacker's posts prior to November 2024, and then accused the "legacy media" of lying by reporting that said attacker was a far right pro-zionist, because deleting evidence solely so you can keep up your culture war grifting is the pinnacle of adhering to free speech

...and because billionaire manchild Elon Musk is so into FREEZE PEACH, he's ranting and raving about the existence of Wikipedia which is apparently "spaghetti carbonara" because it cites sources instead of parroting the version of events he thinks is allowable. Of course, he neglected to mention that his shitty AI program is trained by data scraping from Wikipedia, which just makes it look uncannily like his shitty AI told him some home truths which he didn't like. And guess what? Donations to Wikipedia increased by 450% overnight after Musk's little temper tantrum

...but then billionaire manchild Elon Musk did the impossible and managed to make Laura Loomer of all people look insightful when she called him out for being a MAGA tourist who was only looking to boost his billions, so of course the FREEZE PEACH absolutist responded to this by letting Loomer say her piece. Just kidding, he removed her blue checkmark, demonetise her account while removing all her subscribers, and dispatched Iain Miles Cheong to tell the MAGA faithful that she was now Unpersoned

...soon followed by billionaire manchild Elon Musk calling for more positive, civil discussion on Twitter - a couple of days after calling people "subtards" and suggesting that one critic fuck himself in the face, so apparently the polite, civil conversation is something which his obvious alt Adrian Dittmann should be doing - and does every time Musk glazes his own tweets

...and on the subject of billionaire manchild Elon Musk and his alt account, the daft twunt actually tried to pose as Adrian Dittmann in a Twitter spaces using a voice modifier while speaking exactly like the ketamine-addled fuckwit...while failing to explain why they were in the Twitter Spaces in the first place

...but what says charity like billionaire manchild Elon Musk making a large charitable donation just as the clocks ring in 2025? Well, for one thing, the "charity" not being the Elon Musk Foundation, then it looks a lot like laundering money for tax dodging purposes

Brilliant bit of statesmanship by Yoon Suk Yeol when he declared martial law in South Korea due to opinion polls calling for him to resign or even be impeached and called for the arrest of his political opponents - only for his coup to be put back in its box within six hours and now calls for his impeachment were coming from rival political parties, and with good cause

Frowning thumb Joe Rogan claims that the reason he pivoted hard to support registered sex offender Donald Trump at the election was because Tim Walz lied once, though he hasn't specified when Walz supposedly lied - nor explained why he doesn't have a problem with registered sex offender Donald Trump lying multiple times in the same sentence multiple times a day

Unifying force for good Keir Starmer showed just how devoted to unity he is by appointing a new anti-corruption minister in Margaret Hodge. Yes, the same Margaret Hodge who is the figurehead for a foreign-backed body which sough to overthrow a democratically-elected party leader via a concerted smear campaign. No evidence of corruption or dirty money there!

Odious little turd Wes Streeting said it was a "scandal" that puberty blockers were being given to people who wanted to transition, all while justifying the non-scandalous decision to uphold the TERF manifesto known as the Cass Review without question, in spite there being countless questions to make about the Cass Review

Isn't it funny how the NYPD can act like The Terminator when somebody hops the turnstiles on the subway, but when they need to find the guy who murdered UnitedHealthcare's CEO they turn into Inspector Clouseau?

The increasingly hapless Kemi Badenoch is determined to keep banging on about immigration at PMQs, isn't she? So at which point is it going to occur to her that she was a Minister for the party that was in power between 2010-24 which has pretty much everything to do with the things she's haplessly kvetching about?

...and because Kemi Badenoch is incapable of saying anything without making it another culture war battleground, she then took aim at the mere concept of lunch - though that would explain why she seems to know jack shit about who was in power between 2010-24, as lunch meetings are for the weak according to her, which definitely doesn't make it look remarkably like she was never invited to any during her entire time as a government minister

If there wasn't enough evidence that Wes Streeting is completely devoid of charm, him rocking up to the Spectator awards bash and using his moment on the stand to make a series of jokes at Louise Haigh's expense (when, of course, she wasn't in the building) only continues to prove what a charmless little scrote he is

I'm not sure how Gregg Wallace thought issuing a statement that boiled down to "There were only 13 accusations" which came from "middle class women of a certain age" was the best line of defence after multiple accusations of inappropriate behaviour towards female MasterChef contestants and crew, but that's what he went with

...yet somehow Gregg Wallace was not done (unlike his career) as he followed that up with the usual "I'm sorry you were offended" nonpology where he said that it was stress that caused him to make his previous attempt at a nonpology where he sounded exactly like the sort of misogynistic fuckbucket the allegations against him say that he has been for years

Clueless neanderthal Lee Anderson got his fee-fees hurt when the Have I Got News For You Twitter account made fun of him, so bellowed how "when" Reform Ltd are in power they will shut the BBC down to save the taxpayer billions...when the BBC isn't funded out of taxes, and HIGNFY is produced by Hat Trick Productions so would very quickly find itself snapped up by another channel to continue making funs of utter fucking morons like Anderson

...and then Lee Anderson followed that up by mansplaining to somebody who asked what men have to put up with compared to periods, pregnancy and menopause by suggesting the Battle of the Somme - something which men famously haven't had to put up with since 1916

The toilet-fixated Nancy Mace is now wearing her arm in a sling because she's claiming she was "assaulted" by somebody shaking her hand, which definitely doesn't make her look like an attention-seeking sociopath by any means, especially not when she forgot to log out of her main Twitter account before posing as a member of the public corroborating her clearly made-up story...

So it turns out there's a reason why Honey sounded too good to be true for all the years they were offering affiliation ads to countless Youtubers: because it was a scam where PayPal not only misled users about discounts and creamed the difference off the top, but were also hoarding the money from affiliate links from Youtubers who they paid to advertise their app

It seems that WWE miss the days of pretending they didn't know about the sex predator heading up the company, based on their recent hiring of Lee Fitting in spite his being fired by ESPN for toxic and inappropriate behaviour towards women. Set your watches for another grumpy Triple H saltfest when that question comes up during a press conference

Intellectual heavyweight Lauren Boebert made the following comment: "Because of the political instability in the Middle East, its important to buy the Panama Canal from Egypt"

For once Funko were in the wrong not by rushing out series after series of their figures that risk making stores capsize under the sheer weight of the unsold figures, but instead unwittingly taking Itch IO offline after Brand Shield identified the platform as "phishing" and issued a takedown, because AI can't do anything properly

Gurning messiah complex Mr Beast seems to have real issues with people suggesting his Squid Games knockoff might be a bit shit, most obviously when going off at the IGN reviewer who gave it a two-star review - though at least that did give brief respite from seeing him tweeting in response every single time Netflix tweeted about the second season of Squid Games

In a complete surprise The Hawk Tuah Girl turned out to be a massive crypto scammer whose pump and dump scheme was about as subtle as having a bulldozer dropped on your head from an eighth storey window, given she pulled the rug within hours of announcing her fake ass currency - and when Coffezilla confronted her with the facts, she pretended she was going to bed and let her fellow scammers yell utter gibberish as a means of defence

Looks like Spotify decided to let AI handle everybody's Wrapped this year, so as a result it's telling you that you listened to bands that you didn't listen to and certainly didn't listen to bands you certainly did all because they laid off people whose job it was to compile things so the bosses could pay themselves a little more

Isn't it funny how Eric Bischoff ramped up the anti-AEW rhetoric on his podcast even more than usual just in time for WWE to have him appear on a couple of episodes of NXT? Just a coinkidink, I'm sure...

And finally registered sex offender Donald Trump spent an entire weekend insisting he was president of the USofA and not billionaire manchild Elon Musk, which only serves to make it abundantly clear that he's rattled by the talk of being a puppet candidate that was bought for a fraction of what Apartheid Clyde paid for Twitter