误传
社会化媒体
中国
方案(数学)
计算机科学
特征(语言学)
健康信息
互联网隐私
情报检索
万维网
政治学
计算机安全
医疗保健
数学
语言学
哲学
数学分析
法学
作者
Yuelin Li,Zhenjia Fan,Xiaojun Yuan,Xiu Zhang
标识
DOI:10.1016/j.ipm.2021.102769
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.
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