An Experimental Examination on Techniques to Mitigate the Spread of Misinformation on Social Media Networks

Abstract

Emerging research has focused on finding ways to control the spread of misinformation on SMNs. SMNs have become increasingly weaponized for individual and societal harm. For example, the United States Intelligence Community (USIC) recently released a joint statement with the Department of Homeland Security implicating the Russian government in using major social media networks (SMNs) to influence the 2016 Presidential election with "information warfare" (Clark, 2018). This study focuses on examining SMN features that can potentially reduce the spread of misinformation. Through an experimental survey approach, this study measures the effectiveness of SMN features in influencing misperceptions of SMN users who view misinformed news stories. Prior research has determined that a “related articles” SMN feature can provide context directly under misinformed SMN posts, significantly reducing SMN user misperceptions on controversial topics (Bode & Vraga, 2015). Other studies examined how social interactions on SMNs influence the consumption of content (Messing & Westwood, 2014). Whereas previous studies assessed these SMN features in isolation, this study aims to examine how these SMN features interact with each other in order to reduce the spread of misinformation. This study also examines the social context of SMN using a theoretical framework that integrates social information processing theory and social cognitive theory. More specifically, we examine the impact of social feedback on SMN user perceptions of misinformation. We predict that the combination of these SMN features, which more closely parallel real-world SMN usage, will influence SMN user misperceptions more than any one SMN feature in isolation.