Abstract
Patterns of human actions have attracted increasing attention, since the quantitative understanding of human behavior has important social and economic significance. This paper focuses on behavior patterns of BBS users by conduct analysis on real data of a famous BBS in China. The results show that the reply number of posts and the post number, reply number of users both follow power-law distribution. We further confirm that the one-day reply number of all the users follows power-law distribution at the population level within a certain range. According to the inflection point of the curve, we find out 100 abnormal reply behaviors. Further analysis to the time and space characteristics of the abnormal reply behaviors, we identify 8 artificial hot posts. We find that they have high time similarity, content similarity, structure similarity and show significant signs of human intervention. We infer that the 8 hot posts are the results of network hypes made by online water army. Our findings are meaningful to network public opinion monitoring and may enable a fast detecting of network hypes and online water army.
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Chen, G., Cai, W., Xu, H., Wang, J. (2013). Empirical Analysis of Human Behavior Patterns in BBS. In: Xu, W., Xiao, L., Zhang, C., Li, J., Yu, L. (eds) Computer Engineering and Technology. NCCET 2013. Communications in Computer and Information Science, vol 396. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41635-4_14
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DOI: https://doi.org/10.1007/978-3-642-41635-4_14
Publisher Name: Springer, Berlin, Heidelberg
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