Description
The importance of dealing with fake news on social media has increased both in political and social contexts. While existing studies focus mainly on how to detect and label fake news, approaches to assist users in making their own assessments are largely missing. This article presents a study on how Twitter-users’ assessments can be supported by an indicator-based white-box approach. First, we gathered potential indicators for fake news that have proven to be promising in previous studies and that fit our idea of a white-box approach. Based on those indicators we then designed and implemented the browser-plugin TrusyTweet, which assists users on Twitter in assessing tweets by showing politically neutral and intuitive warnings without creating reactance. Finally, we suggest the findings of our evaluations with a total of 27 participants which lead to further design implications for approaches to assist users in dealing with fake news.
TrustyTweet: An Indicator-based Browser-Plugin to Assist Users in Dealing with Fake News on Twitter
The importance of dealing with fake news on social media has increased both in political and social contexts. While existing studies focus mainly on how to detect and label fake news, approaches to assist users in making their own assessments are largely missing. This article presents a study on how Twitter-users’ assessments can be supported by an indicator-based white-box approach. First, we gathered potential indicators for fake news that have proven to be promising in previous studies and that fit our idea of a white-box approach. Based on those indicators we then designed and implemented the browser-plugin TrusyTweet, which assists users on Twitter in assessing tweets by showing politically neutral and intuitive warnings without creating reactance. Finally, we suggest the findings of our evaluations with a total of 27 participants which lead to further design implications for approaches to assist users in dealing with fake news.