Recognizing fake information through a developed feature scheme: A user study of health misinformation on social media in China

被引:28
|
作者
Li, Yuelin [1 ,2 ]
Fan, Zhenjia [1 ,2 ]
Yuan, Xiaojun [3 ]
Zhang, Xiu [2 ,4 ]
机构
[1] Nankai Univ, Business Sch, Dept Informat Resources Management, Tianjin 300071, Peoples R China
[2] Nankai Univ, Res Ctr Human Informat Behav, Tianjin 300071, Peoples R China
[3] SUNY Albany, Coll Emergency Preparedness Homeland Secur & Cybe, Albany, NY 12222 USA
[4] Tianjin Ren Ai Coll, Tianjin 301636, Peoples R China
关键词
Health information behavior; Health misinformation; Social media; LITERACY; DISINFORMATION; CREDIBILITY; TWITTER; MODEL; LIFE; WEB;
D O I
10.1016/j.ipm.2021.102769
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This study aims at helping people recognize health misinformation on social media in China. A scheme was first developed to identify the features of health misinformation on social media based on content analysis of 482 pieces of health information from WeChat, a social media platform widely used in China. This scheme was able to identify salient features of health misinformation, including exaggeration/absolutes, induced text, claims of being unique and secret, intemperate tone or language, and statements of excessive significance and likewise. The scheme was then evaluated in a user-centred experiment to test if it is useful in identifying features of health misinformation. Forty-four participants for the experimental group and 38 participants for the control group participated and finished the experiment, which compared the effectiveness of these participants in using the scheme to identify health misinformation. The results indicate that the scheme is effective in terms of improving users' capability in health misinformation identification. The results also indicate that the participants' capability of recognizing misinformation in the experimental group has been significantly improved compared to those of the control group. The study provides insights into health misinformation and has implications in enhancing people's online health information literacy. It informs the development of a system that can automatically limit the spread of health misinformation. Moreover, it potentially improves users' online health information literacy, in particular, under the circumstances of the COVID-19 pandemic.
引用
收藏
页数:14
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