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| Health Information Quality in Social Media: An Analysis Based on the Features of Real and Fake Health Information |
| Li Yuelin, Zhang Xiu, Wang Shanshan |
| Department of Information Resources Management, Business School of Nankai University, Tianjin 300071 |
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Abstract The study explores the features of real and fake health information to help improve health information quality in social media. The sample includes 482 pieces of information collected from WeChat. The study first identifies real and fake health information through a three-round process involving rumor identification platforms and health experts. Then, the information was imported to NVivo for open coding to identify the features of real and fake information based on a framework that helps to assess information quality. The study conducted Chi-Square tests to identify significant features of fake information, based on which we can develop a feature list of fake health information. The results indicate that gender and occupation affect users’ real and fake information dissemination behavior. Fake information has some salient features that differentiate it from real information in terms of credibility, accuracy, reasonability, and support. In particular, some features, such as punctuation errors, inappropriate use of space, induced text, mismatch between the title and content, strong personal views, redundancy, incomplete content, and under the guise of authority, are typical of fake health information in the Chinese context. The study develops a feature list for fake health information and provides a tool to identify fake health information in social media. It can also help health information systems to develop some mechanism to screen or delete fake information, in order to improve information quality and online health information environment.
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Received: 02 June 2017
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