Mitigating Confirmation Bias on Twitter by Recommending Opposing Views
This work addresses the issue of echo chambers and polarization for social media users, but it is incremental as it presents preliminary steps without concrete results.
The authors tackled the problem of confirmation bias on Twitter by proposing a content-based recommendation approach to expose users to opposing viewpoints, using the political debate around Donald Trump's presidency as an illustrative showcase.
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.