Breaking Political Filter Bubbles via Social Comparison
CoRR(2024)
摘要
Online social platforms allow users to filter out content they do not like.
According to selective exposure theory, people tend to view content they agree
with more to get more self-assurance. This causes people to live in ideological
filter bubbles. We report on a user study that encourages users to break the
political filter bubble of their Twitter feed by reading more diverse
viewpoints through social comparison. The user study is conducted using
political-bias analyzing and Twitter-mirroring tools to compare the political
slant of what a user reads and what other Twitter users read about a topic, and
in general. The results show that social comparison can have a great impact on
users' reading behavior by motivating them to read viewpoints from the opposing
political party.
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