News Recommendation for China Sina Weibo Microblog Service Based on User Social Behaviors

News Recommendation for China Sina Weibo Microblog Service Based on User Social Behaviors

Zuo Yuchu, You Fang, Wang Jianmin, Zhou Zhengle
DOI: 10.4018/978-1-4666-4695-7.ch010
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Abstract

Sina weibo microblog is an increasingly popular social network service in China. In this work, the authors conducted a study of detecting news in Sina weibo microblog. They found the traditional definition for news can be generalized here. They first expanded the definition of news by conducting user surveys and quantitative analysis. The authors built a news recommendation system by modeling the users, classifying them into four different groups, and applying several heuristic rules, which derived from the generalized definition of news. By applying the new recommendation system, people got newsworthy information, while the funny and interesting tweets, which are popular in Sina weibo microblog, were put in the last ranking list. This study helps us achieve better understanding of heuristic rules about news. Some official organizations can also benefit from the work by supervising the most popular news around civilians.
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In previous content-based classification researches which mainly center on the Chinese sentence structure and syntax analysis, we encountered such a fatal bottleneck: constantly newly-emerged words and usages. In fact, such a problem results from the complexity and flexibility of Chinese which is so different from English. Even some researchers solve this problem by building mathematical model (Abdullah & Wu, 2011), considering users’ relations in social network(Magnani, Montesi, & Rossi, 2010), or combining social network with RSS feeds (Phelan, McCarthy, Bennett, & Smyth, 2011a, 2011b; Phelan, McCarthy, & Smyth, 2009) (though they only recommend RSS news by tweets, we can easily reverse the idea by recommending tweets by RSS feeds), a subtle problem which is omitted is that people use microblog not only for the news which would appear on every portal site, but also for some social purpose (Chen, Nairn, & Chi, 2011; Zhao & Rosson, 2009).

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