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Evaluation of Microblog Users’ Influence Based on PageRank and Users Behavior Analysis

机译:基于PageRank和用户行为分析的微博用户影响力评估

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This paper explores the uses’ influences on microblog. At first, according to the social network theory, we present an analysis of information transmitting network structure based on the relationship of following and followed phenomenon of microblog users. Informed by the microblog user behavior analysis, the paper also addresses a model for calculating weights of users’ influence. It proposes a U-R model, using which we can evaluate users’ influence based on PageRank algorithms and analyzes user behaviors. In the U-R model, the effect of user behaviors is explored and PageRank is applied to evaluate the importance and the influence of every user in a microblog network by repeatedly iterating their own U-R value. The users’ influences in a microblog network can be ranked by the U-R value. Finally, the validity of U-R model is proved with a real-life numerical example.
机译:本文探讨了使用对微博的影响。首先,根据社交网络理论,基于微博用户的关注与关注现象的关系,对信息传输网络的结构进行了分析。在微博用户行为分析的指导下,本文还提出了一种计算用户影响权重的模型。它提出了一个U-R模型,通过该模型我们可以基于PageRank算法评估用户的影响并分析用户的行为。在U-R模型中,探讨了用户行为的影响,并通过重复迭代自己的U-R值,将PageRank用于评估微博网络中每个用户的重要性和影响。可以通过U-R值对用户在微博网络中的影响力进行排名。最后,通过一个实际的数值例子证明了U-R模型的有效性。

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