digitalemens

[digitalemens]

blog 10/11/20

With social network analysis you can analyse the coherence between subjects and/or objects. This is not done in isolation, but in constant interaction. You can analyse different kinds of relationships between those subjects or objects: similarities (e.g. location, activities, characteristics…), roles or functions (e.g. hierarchical relationships), cognitions (e.g. how well do each subject know the other, is it a like or hate relationships…), events (e.g. do the subjects share information, do they interact, are there transactions…).  With social network analysis, it is possible to make statements about the individuals (nodes) and where they stand withing the network, about the relationships between individuals or about the structure of the network itself.

Within my field of study, communication sciences, social network analysis could be used to explore the potential for online extremism. Crawling a social networking platform like YouTube has the potential to find content and interaction that is aimed at radicalizing people who might not have extreme opinions to begin with. Analyzing extremists networks on YouTube could be done in combination with sentiment analysis, to identify users and groups in the network and their positive and negative emotions/opinions towards the extreme content.

[digitalemens]

blog class 20/10

Comparison of word use from newspapers from the UK. - tabloids vs broadsheets

(blog will be adjusted soon)

[digitalemens]

Blog - class 6/12/2020

I made a visualization of the number and location of zero-waste shops around Europe. I did not use RAWGraphs, but I used ‘datawrapper’ instead. This visualisation becomes interactive if you click on the link below. 

If you look at this map and zoom in, it looks like zero-waste shops are rather popular in Germany, Switzerland, Northern Italy and Belgium. In other countries in Europe zero-waste stores are more rare. Making a visualization of the stores and their locations could make the search for these stores more easy. It could also become more attractive for people who don’t go to these stores yet. Furthermore, this map could also be useful for people who want to open a zero-waste shop.

In general, using this data and making a visualization could promote the reduction of (plastic) packaging waste production and consumption.

http://datawrapper.dwcdn.net/EjbOm/1/

[digitalemens]

Blog post - class 29/09/2020

During this class we learned the basic concepts of statistics. We also learned basic methods of descriptive statistics: tabular, graphical and numerical method. In addition to this, we were thought the different data visualizations (bar chart, pie chart, histogram, line graph and scatter plot) and which visualization belonged to each method.

After learning about the basics of statistics and data visualization, we got to practice this in excel, which I found really useful. We learned a few basic tricks in excel, e. g. how to make a sum of total automatically, and we learned how to do a visualization in excel (historgram, line graph, scatter plot…). A really important tip we got is how to make a dashboard with your data visualizations. Knowing how to do this is a great asset in the work field.

[digitalemens]

Blog 3 - class 22/09/20

As we discussed in class, I think (big) data has a lot of potential for changing the world for the better. That is, of course, if the data is used for the right things, in the right way, by the right people with good intentions. For example, I think that big data can be very useful for providing solutions or bringing problems to the surface in several different areas. Take for example the Aqueduct project, which uses data to indicate change in water supply,  water demand, water stress etc. over the world. Data here seems to be put in use for the greater good. Or consider the Green Book mapping. Here, data is used to bring awareness, which is also a good cause. In these cases, the power of data is put to use for good practices.  

On the other hand, you can also think about the potential ethical problems of the power of (big) data. Lack of privacy and transparency are common problems that arise, especially with companies that monetize data. Then again, these problems lay mostly in the hands of the people (or companies) that misuse data rather than it being a problem of the power of data itself. 

But if you consider the power of data itself, there are a few things to discuss as well. So to say that big data are as powerful that it speaks for itself (as is said by Chris Anderson) is a rather unnuanced point of view, in my opinion. Data can still be wrong and in many cases, data needs to be interpreted in the right context (as is the case with the risk assessment tool from which the scores proved remarkably unreliable in forecasting violent crime). This is why I think data will always need a human side as well, that is: a human side with the competence of critical thinking and awareness.

[digitalemens]

Blogpost 2 - class 15/09/20

First article: Tuters, M., de Keulenaar, E., Kisjes, I., Bach, D., & Beelen, K. (2019). The intellectualization of online hate speech: Monitoring the Alt-Right audience on YouTube.  https://dev.clariah.nl/files/dh2019/boa/0768.html

Second article: Ben-David, A., & Matamoros-Fernández, A. (2016). Hate speech and covert discriminations on social media: Monitoring the Facebook pages of extreme-right political parties in Spain. International Journal of Communication, 10, 1167-1193.

The first article discusses the use of hate speech and extreme speech on YouTube. The data in this article consists of channel references, tags, video titles and all the comments made by individual users of YouTube on the right-wing YouTube channels. It could be argued that this article belongs to the Digital Humanities field because the subject of the article (and the objective of their research) belongs to the Humanities field, while the method they used for this research takes a digital approach.

The research looks into the potential problem of YouTube as a platform that normalizes political extremes. The researchers look at more than the obvious hate speech terms, that are characterized as a typical byproduct of the extreme-right. They also take into account pseudo-intellectual expressions. They hypothesize that commenters on YouTube moved from hate speech to extreme speech. The authors, furthermore, examine the audience over time to get an insight in the potential effects of the platform (how the beliefs and behaviours of the consumers shift as a result of the content that they engage with). They believe that this research calls for computational techniques sensible to the ambiguity of online hate speech. They gathered the data (video titles, channel references, tags and comments) using the YouTube Data Tool (/YouTube API).

The second article also discusses the use of hate speech on a social media platform, this time Facebook. It also considers the role of the platform’s policy and its technological affordances. The data that is analyzed here comes from the Facebook pages of seven extreme-right political parties and consists of text (words), images and links. The researchers aimed to examine the circulation of hate and discrimination on Facebook within the legitimate boundaries of the political discourse in Spain. This suits the humanities field. To conduct their research, they used digital tools and software (e.g. Netvizz), which is why it could be argued that this belongs to the digital humanities field. They argue that researchers should focus on practices and content as well as the specific features of the technology of social media, which contributes to their choice of using digital tools to conduct their research.

Both articles consider the social media platform as a potential problem for shaping an infrastructure for the circulation of subtle associations of hate and discrimination, even though both platforms officially prohibit explicit hate speech. However, the focus on content is different (the first article focuses mainly on the consumers whereas the second also takes into account the content of the pages itself and not only the content of the consumers of those pages). They both use API’s to gather their data but also use different methods and tools to conduct their research.

[digitalemens]

Introduction course - 8/09/20

As an exchange student from Belgium, the first course was very interesting to me. First of all, at my faculty at my home university (KU Leuven) I never had a course that lasted for four hours. In addition, I've never had a course consisting of two different topics combined into one course, as is the case for the Digital Humanities course. At the start of the lesson we got an introduction to the Digital Humanities content followed by an introduction of the Career Management Skills courses, which are part of the Digital Humanities course. I think it will be very interesting and instructive to apply what we learn during the Digital Humanities course to our own career management skills. I’m intrigued to learn more about both aspects of this course and to see where this will get me in the long run. 

During the first class we also followed an introduction lesson to Wordpress. Nevertheless, I decided to make my blog on Tumblr instead. I am planning, however, on learning how to work with Wordpress as well.

The end of the first class consisted of a guest lecture, during which several specific cases of his experience as a digital consultant were shown.