Yesterday was the vitual launch of the wonderfully edited (eds. Martin Engebretsen & Helen Kennedy) volume of Data Visualization in Society. Together with Daniela van Geenen I contributed a chapter about approaching data visualizations as interfaces to data in various ways to the volume. So happy to see this in print (and open access). It’s been a wonderful ride.
The last four days I spent in Barcelona, attending the ACM conference on Fairness, Accountability, and Transparency. What a ride it has been! It was my first time at FAT*/FAccT and it has been absolutely amazing and inspiring. When I started my PhD it was my goal to get accepted to the FAT* (now ‘FAccT’) conference with my work. Not only did I get accepted, I was also awarded wih the best student paper award. It still feels a bit surreal, but I am so happy, honored, and thankful to have been given this opportunity and to see that my work resonates with this wonderful community.
You can find my paper here: https://dl.acm.org/doi/abs/10.1145/3351095.3372833
The presentation will be uploaded to YouTube in the coming days, and you should be able to find it here: https://www.youtube.com/channel/UCs16j6ot-CYq-ZqYpO-vqMg
Our (w. Eef Masson & Karin van Es) paper on data walks in education is out now. You can find it here: https://www.digitalcultureandeducation.com/volume-11
Together with Iris Muis, Gerwin van Schie and Tim de Winkel we wrote the article ‘”Liberation begins with stating the facts”: rationalization of discrimination through data in populist rhetoric on Twitter’. It considers Geert Wilders’ use of numbers and statistics about immigrants on Twitter. The article is open access and can be found here: http://doi.org/10.16995/olh.320
Geert Wilders is internationally the most iconic politician of the Netherlands and one of the most mediagenic flag bearers of Europe’s new right. This paper presents an analysis of a fundamental aspect of Wilders’ claims, namely their apparently factual basis, by employing framing theory and contentious politics theory, and taking a mixed method approach of quantitative data analysis and qualitative critical reading of Wilders’ Twitter timeline. Our main research question is: How did Geert Wilders frame his political claims, specifically about race and ethnicity, through statistics, numbers, and ‘facts’ on Twitter in the three months leading up to the Dutch elections on 15 March 2017? Our aim is to take Geert Wilders as a case study to closely examine how politicians can frame a particular topic to suit their own purposes, and manifests itself when politicians move to the new media sphere where their views seem to be less frequently challenged and their statements less verified by the media. We will conceptualize Wilders’ Twitter practice as ‘information bricolage’ which is a consequence of the new media reality where, on his own Twitter feed, a politician appears to be the editor of his own news. We show how the Partij voor de Vrijheid (PVV) campaign is almost in its entirety Wilders’ media performance, and how this is, both online and offline, largely devoid of conversation but consists of one-way broadcasting instead. In addition, Wilders shows a paradoxical attitude towards statistics. On the one hand, he challenges the objectivity of numbers or the institutes that produce them, while at the times he uses these ‘facts’ to validate his statements. By way of these practices, Geert Wilders rationalizes and legitimizes discriminating claims about Dutch immigrant populations.
The past few weeks I’ve been working on the query design for my systematic review on algorithmic accountability. I encountered two problems:
- ‘Algorithmic accountability’ is a relatively new term, whereas the problems, themes, concepts which are connected with it, are ofcourse touched upon in earlier work in various disciplines;
- I wanted to find a systematic way to approach the query design, which also accounts for the diversity of the fields and terms used to discuss matters related to algorithmic accountability.
I eventually settled on the following approach, using computational methods. Out of the material that was identified as relevant prior to the review, only the articles (27) which included keywords were selected for this exploration.From these articles the collocations of the keywords were extracted.
In charting the keywords’ collocations, first the individual keywords were related to the other keywords of the article. For instance if the keywords of an article are ‘big data’, ‘algorithms’, and ‘accountability’, then the relations would be mapped as follows:
big data –> algorithms
big data –> accountability
algorithms –> big data
algorithms –> accountability
accountability –> big data
accountability –> algorithms
After the relations were prepared, these collocations were mapped in Gephi.
The nodes with the most incoming/outgoing connections (degree >= 35) were then filtered out.
This value of mapping these keywords, is that it gives some perspective on what terms are used in what fields (or, more accurately: with what other kinds of terms, thereby hinting at the field). Four (very rough) clusters could be detected by modularity: one revolving around governance (e.g. government, governance, accountability – though there are also smaller nodes refering to, for instance, journalism). The second cluster deals mainly with legal aspects (e.g. GDPR, right to explanation), the third deals with more general data-related issues (e.g. regulation, automation, surveillance). The last is predominantly dealing with ethics. The interesting thing about this last cluster is that aside from the ethics node, all other nodes in this cluster are from 1 paper (this paper had a lot of keywords, thereby constituting its own cluster) – which also hints at the limitations of this method on its own.
While the mapping provides some insight into which terms are used in what kinds of debates, it doesn’t really point as of yet to what combinations might be fruitful for query design. Thus, subsequently, the edges table was exported from Gephi, and the edge weight was used as a measure to determine the strength of the relations between keywords. The double relations (a –> b / b –> a) were resolved and their edge weight was added together.
Now, I have a systematic basis for deciding upon my query, for I can demonstrate which terms seem to be more strongly connected. Which doesn’t mean that likely it’s still going to be hard, but atleast I have some more grounding!
The past few days, I’ve been attending the Digital Tools & Uses Conference in Paris, where I was part of the Web Studies track. I’ve presented the Tool Criticism paper I’ve written together with Karin van Es and Mirko Tobias Schäfer. Our paper is published in the ACM proceedings, and can be found here. It’s been a great opportunity to talk about our ideas with other scholars/scientists!
This summer has so loaded with great events and activities, it’s been hard to keep track. Here’s an overview of some of my academic summer’s highlights.
Data visualization in society seminar
I’m really thrilled to be writing a chapter together with Daniela van Geenen for Helen Kennedy and Martin Engebretsen’s book project Data visualization in Society. Part of the project was a great seminar at the University of Agder’s study centre Metochi on Lesbos. This was a great way to get feedback on one’s work, and to streamline the book in its entirety. I feel this is going to be a really great book for practitioners, students and academics.
Gephi Field Notes plugin, developments and talk at KCL
Another thing I’m quite passionate about is the development of the Gephi Field Notes plugin. Together with the Digital Humanities Lab and the Gephi developers we’re trying to finetune the plugin. Moreover, we got to give a talk at King’s College London about the plugin. Really great to be meeting so many people who – like we – are really exicted about this project.
Arduino Workshop at the Datafied Society
Karin van Es organized an Arduino Workshop by Creative Coding Utrecht at the Datafied Society, and it was absolutely great. It was so much fun to solder again, and to tweak with the little wires, LEDs and resistors. Going to be doing a lot more if this I hope. In any case, we want to develop some Arduino setups for our students to use for data gathering on data walks.
Of course, summers are mainly for research. Thus, I’ve been doing a *lot* of writing these past weeks. See also my Research projects to get an idea of what I’m currently working on. Spoiler: it’s a lot.
Meeting my new colleagues
With so many great things going on, you’d almost forget that I’m starting my Ph.D. project in September! I was really happy to meet my new colleagues during a Ph.D. meetup at the end of June. We got to do some fun activities and get to know one another (and the city) a little better.
Upcoming UDS Summer School
Before starting my Ph.D. I have the pleasure to teach in the Utrecht Data School Summer School. We’re really excited that we’re opening up the summer school to external students as well, and we’re really happy with the turnout. I’m looking forward to teaching a lot of (future) students a crash course in digital methods.
Daniela van Geenen and myself had the pleasure to present the work we have done, together with Karin van Es and Jelmer van Nuss, on the Gephi Field Notes Plugin at the Data Justice Conference 2018. We had a great time in Cardiff, and were happy to receive so much great feedback on the project. The paper will be published in the Good Data book, the plugin can be found on GitHub.
Our new article ‘Political topic-communities and their framing practices in the Dutch Twittersphere’ is now published in Internet Policy Review! I had the pleasure to work together with Daniela van Geenen, Mirko Tobias Schäfer and Ludo Gorzeman on this one. The paper came forth out of commissioned research for Vrij Nederland and Nieuwsuur. In the paper we discuss how politically interested topic communities engage with news (media).
In light of the need for political plurality and informed debate this study questions information distribution and curation on Twitter. We contribute to the understanding of ideological homophily by exploring the notion of the ‘echo chamber’. Using a sample of two weeks of Dutch Twitter data, we combine network analysis of retweet networks, with qualitative reading and categorisation of engagement with media content in tweets within political topic communities. We found that media references were predominantly framed in affirmative ways in relation to the referenced medium content. Our findings show that users consciously select media messages that correspond with the general sentiment within their topic community, or frame them accordingly. We see this as a willful ‘echo chamber’, or a ‘repillarisation’.