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Measuring Micro-blogging User Influence Based on User-Tweet Interaction Model

机译:基于用户推文交互模型测量微博用户影响

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Measuring micro-blogging user influence is very important both in economic and social fields. In this paper, we propose a user-tweet interaction model to describe the relationships among users and tweets. Considering the time affect, TAC(time-effectiveness attenuation coefficient) is proposed when calculating tweet influence which consists of retweet influence and comment influence. Then we make a detail analysis on the generation of user influence which consists of post influence and follow influence based on the results of tweet influences. We also discuss the correlation between post influence and follow influence by use of Spearman's rank correlation coefficient. At last, we rank users by calculating the bias spatial distances. Taking Sina micro-blogging as background, after a series of experiments, we believe that our method is accurate and comprehensive when measuring the influences of micro-blogging users.
机译:在经济和社会领域,测量微博用户的影响非常重要。在本文中,我们提出了一个用户推文交互模型来描述用户和推文之间的关系。考虑到时间影响,在计算包括转关影响和评论影响的推文的影响时,提出了TAC(时间效能衰减系数)。然后我们对用户的影响进行详细分析,这包括后影响和基于推文影响的结果遵循影响。我们还讨论了后面影响力与使用Spearman等级相关系数的影响。最后,我们通过计算偏差空间距离来排名用户。以新浪微博博客作为背景,在一系列实验之后,我们认为,当测量微博用户的影响时,我们的方法是准确和全面的。

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