Intelligent nudging for truth: Mitigating rumor and misinformation in social networks with behavioral strategies

Abstract

Social networks play a crucial role in disseminating information during emergencies and natural disasters, but they also facilitate the spread of rumors and misinformation, which can have adverse effects on society. Numerous false messages related to the COVID-19 pandemic circulated on social networks, causing unnecessary fear and anxiety, and leading to various mental health issues. Despite strict measures by social network providers and government authorities to curb fake news, many users continue to fall victim to misinformation. This highlights the need for novel approaches that incorporate user participation in mitigating rumors on social networks. Since users are the primary consumers and spreaders of information, their involvement is essential in maintaining information hygiene. We propose a novel approach based on nudging theory to motivate users to post or share only verified information on their social network profiles, thereby positively influencing their information-sharing behavior. Our approach utilizes three nudging strategies: Confront nudge, Reinforcement nudge, and Social Influence nudge. We have developed a Chrome browser plug-in for Twitter that prompts users to verify the authenticity of tweets and rate them before sharing. Additionally, user profiles receive a rating based on the average ratings of their posted tweets. The effectiveness of this mechanism was tested in a field study involving 125 Twitter users over one month. The results suggest that the proposed approach is a promising solution for limiting the propagation of rumors on social networks.