Abstract
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.
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Liu, D., Wu, Q., Han, W. (2013). Measuring Micro-blogging User Influence Based on User-Tweet Interaction Model. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38715-9_18
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DOI: https://doi.org/10.1007/978-3-642-38715-9_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38714-2
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