Distortions of political bias in crowdsourced misinformation flagging.

ABSTRACT: Many people view news on social media, yet the production of news items online has come under fire because of the common spreading of misinformation. Social media platforms police their content in various ways. Primarily they rely on crowdsourced 'flags': users signal to the platform that a specific news item might be misleading and, if they raise enough of them, the item will be fact-checked. However, real-world data show that the most flagged news sources are also the most popular and-supposedly-reliable ones. In this paper, we show that this phenomenon can be explained by the unreasonable assumptions that current content policing strategies make about how the online social media environment is shaped. The most realistic assumption is that confirmation bias will prevent a user from flagg

SUBMITTER: Coscia M 

PROVIDER: S-EPMC7328405 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature