2018/09/11 by Elisabeth Lex, Lex, Elisabeth, Mario Wagner +3 · 1 citation
Computer Science · Physics and Astronomy · Social Sciences · #Expert finding and Q&A systems #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Misinformation and Its Impacts #Opinion Dynamics and Social Influence #Social and Information Networks (cs.SI) #cs.IR #cs.SI
paper · pdf · doi:10.48550/arxiv.1809.03901
European Symposium on Computational Social Science, Cologne, Germany
arxiv created 2018/09/11 · openalex publication_date 2018/09/11 · arxiv updated 2018/09/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this work, we propose a content-based recommendation approach to increase exposure to opposing beliefs and opinions. Our aim is to help provide users with more diverse viewpoints on issues, which are discussed in partisan groups from different perspectives. Since due to the backfire effect, people's original beliefs tend to strengthen when challenged with counter evidence, we need to expose them to opposing viewpoints at the right time. The preliminary work presented here describes our first step into this direction. As illustrative showcase, we take the political debate on Twitter around the presidency of Donald Trump.