Mitigating Confirmation Bias on Twitter by Recommending Opposing Views

Publikation: Beitrag in einer FachzeitschriftArtikelForschungBegutachtung

Abstract

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.
Originalspracheenglisch
Aufsatznummer arXiv:1809.03901
FachzeitschriftarXiv.org e-Print archive
DOIs
PublikationsstatusVeröffentlicht - 11 Sep 2018
VeranstaltungEuropean Symposium on Societal Challenges in Computational Social Science: Bias and Discrimination - Köln, Deutschland
Dauer: 5 Dez 20187 Dez 2018

Schlagwörter

    Dies zitieren

    Mitigating Confirmation Bias on Twitter by Recommending Opposing Views. / Lex, Elisabeth; Wagner, Mario; Kowald, Dominik.

    in: arXiv.org e-Print archive, 11.09.2018.

    Publikation: Beitrag in einer FachzeitschriftArtikelForschungBegutachtung

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