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New interdisciplinary research project!

(crosspost from http://vanatteveldt.com/JEDS/)

We were delighted to hear that JEDS/NWO decided to accept our grant proposal for studying personalised online news consumption! In the coming years, our team from the VU, UvA, CWI, and e-Science Center will automatically measure and analyse personalised online news consumption to find out whether online filter bubbles really exist and what effect they have on political knowledge and attitudes.

Team:

  • Wouter van Atteveldt (VU, Communication Science)
  • Laura Hollink (CWI)
  • Damian Trilling (UvA, Communication Science)
  • Antske Fokkens (VU, Computational Lexicology)
  • Judith Möller (UvA, Communication Science)
  • Kasper Welbers (VU, Communication Science)
  • Natali Helberger (UvA, Law)
  • E-science Engineer (NLeSC)
  • Ph.D. Student (VU & UvA)

Abstract:

Online and mobile news consumption leaves digital traces that are used to personalize news supply, possibly creating filter bubbles where people are exposed to a low diversity of issues and perspectives that match their preferences. Filter bubbles can be detrimental for the role of of journalism in democracy and are therefore subject to considerable debate among academics and policymakers alike. The existence and impact of filter bubbles are difficult to study because of the need to gather the digital traces of individual news consumption; to automatically measure issues and perspectives in the consumed news content; and to combine and analyse these heterogeneous data streams.

Work packages:

  • WP1: Develop a mobile app to trace individual news consumption and gather user data;
  • WP2: Create a custom NLP pipeline for automatically identifying a number of indicators of news diversity in the news content;
  • WP3: integrate and analyze the resulting heterogeneous data sets;
  • Use the resulting rich data set to determine the extent to which news recommender algorithms and selective exposure leads to a lower diversity of issues and perspectives in the filter bubbles formed by news supplied to and consumed by different groups of users (WP4).

These analyses allow us to determine the impact of biased and homogeneous news diets on political knowledge and attitudes. The software developed in this project will be open source and re-usable outside the scope of this project by scholars interested in mobile behavior and news production and consumption.

Programming for Communication Scientists (video, 3:55, in Dutch)

De Minor Programmeren van de UvA heeft wetenschappers uit verschillende disciplines gevraagd waarom zij het belangrijk vinden om te kunnen programmeren (alle filmpjes hier). Samen met collega Anne Kroon leg ik uit hoe programmeerkennis ons helpt om het huidige medialandschap te analyseren – en waarom het leuk is om dat te doen.

Finally, some updates.

The last months, I was so busy with all kind of stuff – teaching, publishing some papers based on my research, and giving some talks and interviews – which unfortunately made me a bit sloppy in putting all of what was happening on my website. But by now, everything should be updated. Have a look around!

Some media attention…

This weekend, there was a lot of media attention on Filter Bubbles. On Friday, quality newspaper Trouw published a two-page story based on interviews with me and some colleagues. We tried to make the point that filter bubbles– at least in the Netherlands, at this point in time – are less of a problem than often assumed.

On Saturday, I was interviewed on Radio 1 (Argos) about the same topic, as well as about political microtargeting. You can listen to the fragment here.

Coincidentally, and not related to our project, also quality newspaper de Volkskrant published a large story on Filter Bubbles related to music. It discussed the relationship between the usage of Spotify and music taste, and also hinted at the need for diversity in a music recommendation algorithm, to prevent it from becoming ‘boring’.

Teaching news: New Master Data Science

These weeks, I was co-teaching with Stevan Rudinac the two-week case “Political Communication” as part of the Course “Fundamentals of Data Science”, which is the first course of the new master Data Science at the UvA. The students were analyzing tweets about the US election campaign. A very nice example of interdisciplinary co-operation!

 

New publication on news sharing

I’m happy to announce that our article on news sharing has just been published. From the abstract:

People increasingly visit online news sites not directly, but by following links on social network sites. Drawing on news value theory and integrating theories about online identities and self-representation, we develop a concept of shareworthiness, with which we seek to understand how the number of shares an article receives on such sites can be predicted. Findings suggest that traditional criteria of newsworthiness indeed play a role in predicting the number of shares, and that further development of a theory of shareworthiness based on the foundations of newsworthiness can offer fruitful insights in news dissemination processes.

Trilling, D., Tolochko, P., & Burscher, B. (2016). From newsworthiness to
shareworthiness: How to predict news sharing based on article characteristics. Journalism & Mass Communication Quarterly, online first. doi:10.1177/1077699016654682