A User Study on the Feasibility of Topic-aware Misinformation Warning on Social Media

• Published in: Proceedings of the Human Factors and Ergonomics Society Annual Meeting Vol. 66; no. 1; pp. 621 - 625
• Main Authors: Xie, Jingyi, Yamashita, Michiharu, Cai, Zekun, Xiong, Aiping
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01-09-2022
• ISSN: 2169-5067; 1071-1813; 2169-5067
• DOI: 10.1177/1071181322661252

Misinformation is one of the most fundamental problems in social media with increasing cases and underlying harmful effects on users. To mitigate such problem, misinformation warnings have been developed, including alerting with warning messages and hiding the contents. Previous studies mainly explored the most effective, one-size-fits-all design. Therefore, little has been known about customizable and flexible warning designs. In this study, we propose a “topic-aware misinformation warning” where users’ preferences for warning designs can vary on topics. To illustrate our ideas, we developed Twitter-like pages using three topics (i.e., politics, gossip, and Covid-19) and three designs (i.e., interstitial, contextual, and highlight). We conducted semi-structured interviews with 18 participants to explore their preferences and opinions on the designs. Our results show that users’ preferences for misinformation warnings are diverse in topics. Thus, topic-aware misinformation warning is promising to alleviate misinformation problems on Twitter.