Selective rating: partisan bias in crowdsourced news rating systems

Crowdsourced news rating systems have been suggested as a solution to reducing the amount of misinformation online audiences see. This study expands previous research crowdsourcing by looking at how characteristics of the rating system affect user behavior. In an experiment (N= 1,021), two parameter...

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Bibliographic Details
Published inJournal of information technology & politics Vol. 19; no. 3; pp. 360 - 375
Main Author Duncan, Megan
Format Journal Article
LanguageEnglish
Published Abingdon Routledge 03.07.2022
Taylor & Francis Ltd
Subjects
Bias
corrective action hypothesis
Credibility
Crowdsourcing
Crowdsourcing ratings
False information
Internet
Misinformation
News
news credibility
partisan news audiences
Partisanship
Ratings & rankings
selective expression
survey experiment
User behavior
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Summary:Crowdsourced news rating systems have been suggested as a solution to reducing the amount of misinformation online audiences see. This study expands previous research crowdsourcing by looking at how characteristics of the rating system affect user behavior. In an experiment (N= 1,021), two parameters of the rating system were manipulated. First, users were shown different varieties of news brands on the "menu" they were asked to rate. Second, participation was mandatory for half and voluntary for others. Results indicate partisans rated more news brands when they saw an ideologically dissimilar news menu than one that matched their ideology. Further, the trustworthiness rating of the mainstream news menu decreased when participants had a choice to participate rather than were forced. These results have important implications for understanding how users participate in crowdsourcing news credibility.
ISSN:1933-1681
1933-169X
DOI:10.1080/19331681.2021.1997867