Abstract.
Content analysis is a useful tool for better understanding how different portrays of public health issues may affect news dissemination. In this research, we conducted a content analysis on health-related messages published by opinion-leading news outlets. We examined generic content attributes, including number of words, sentences, images, links, and published time, as well as content valence features. Our findings show that there are no significant differences in the amount words, sentences and hyperlinks used between the highly forwarded and lowly forwarded news posts when covering a public health issue. Whereas the topic and title length as well as content valence of highly forwarded new posts is different from the lowly forwarded ones. We also discuss ways to improve popularity of health-related news.
This work is supported by National Natural Science Foundation of China under Grant No.71171068.
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Pei, J., Yu, G., Shan, P. (2016). Social Media Coverage of Public Health Issues in China: A Content Analysis of Weibo News Posts. In: Latifi, S. (eds) Information Technology: New Generations. Advances in Intelligent Systems and Computing, vol 448. Springer, Cham. https://doi.org/10.1007/978-3-319-32467-8_11
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