Discovering fake news embedded in the opposing hashtag activism networks on Twitter: #Gunreformnow vs. #NRA

Abstract

Abstract After Russia’s malicious attempts to influence the 2016 presidential election were revealed, “fake news” gained notoriety and became a popular term in political discourses and related research areas. Empirical research about fake news in diverse settings is in the beginning phase while research has revealed limitedly that “what we know about fake news so far is predominantly based on anecdotal evidence.” The purpose of this study is to investigate fake news included in politically opposing hashtag activism, #Gunreformnow and #NRA (The National Rifle Association). This study attempted to lay out the process of identifying fake news in the hashtag activism network on Twitter as a two-step process: 1) hashtag frequency analysis, top word-pair analysis, and social network analysis and 2) qualitative content analysis. This study discovered several frames through a qualitative approach. One of the prominent fake news frames was intentionally misleading information that attacks the opposing political party and its advocators. The disinformation tweets overall presented far-right wing ideologies and included multiple hashtags and a YouTube video to promote and distribute their agendas while calling for coalition of far-right wing supporters. However, the fake news tweets often failed to provide a reliable source to back up credibility of the content.