Predicting information popularity: A study of sina weibo

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Conference Proceeding

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In this paper, we explore if information characteristics, including accuracy, familiarity, fluency, importance, informativeneΒ and relevance, can predict the popularity of a meΒage posted and reposted on Sina Weibo, the most popular social media platform in mainland China. Based on past literature, we propose that the factors mentioned above can determine the likelihood that information is spread through various social media venues. But, it is under explored if the relationships between these factors and information popularity would remain in the context of Sina Weibo. In an experiment, we use actual Weibo posts to test the effects of these characteristics on information popularity, operationalized as reposting likelihood. The results show that a short meΒage perceived as familiar, objective, and relevant to oneself would be more likely to be forwarded. Subjects also indicate that boring, implausible, and useleΒ information would be leΒ popular while interesting information would be more viral online. Finally, we provide theoretical and practical implications.

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ACM International Conference Proceeding Series

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