Dresden 2020 – scientific programme

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SOE: Fachverband Physik sozio-ökonomischer Systeme

SOE 13: Focus Session: Opinion Formation

SOE 13.2: Talk

Thursday, March 19, 2020, 09:45–10:00, GÖR 226

Do filter bubbles contribute to opinion polarization in online social networks? Insights from opinion-dynamics modeling. — •Michael Mäs — University of Groningen, Groningen, The Netherlands

Political events such as the Brexit referendum, the election of Donald Trump, and the success of populists in democratic elections have sparked public and scholarly discussion about the effects of online-communication technology on public debate and collective decision-making. In particular, it has been warned that personalization algorithms installed in online social-networks, and search engines contribute to the formation of so-called `filter bubbles'. These bubbles isolate users from information that challenges their views and expose them to content that is in line with their opinions. It has been warned that this contributes to opinion polarization, a dynamic where competing political camps develop increasingly opposing political views. Here, I summarize research on the relationship between personalization and polarization. While I echo the warning that personalization can affect societal processes, I demonstrate that we leap to conclusions when we propose that personalization is responsible for increased polarization. Analyzing models of opinion dynamics in networks, I show that we lack crucial empirical insight into the microprocess of social influence and the aggregation of repeated influence to macroprocesses of opinion polarization.