Abstract
Water army is prevalent in social networks and it causes harmful effect to the public opinion and security of cyberspace. This paper proposes a novel water army groups detection method which consists of 4 steps. Firstly, we break the virtual community into a series of time windows and find the suspicious periods when water army groups are active. Then we build the user cooperative networks of suspicious periods according to user’s reply behaviors and cluster them based on their Cosine similarity. After that, we prune the cooperative networks by just remaining the edges whose weight is larger than some threshold and get some suspicious user clusters. Finally, we conduct deeper analysis to the behaviors of the cluster users to determine whether they are water army groups or not. The experiment results show that our method can identify water army groups on virtual community efficiently and it has a high accuracy.
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Acknowledgement
This research is supported in part by the National Key Basic Research and Development Plan (Grant No. 2013CB329600), National Natural Science Foundation of China (Grant No. 71503260) and Natural Science Foundation of Shaanxi Province (Grant No. 2014JM8345).
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Chen, G. et al. (2016). Detection and Analysis of Water Army Groups on Virtual Community. In: Xu, W., Xiao, L., Li, J., Zhang, C. (eds) Computer Engineering and Technology. NCCET 2015. Communications in Computer and Information Science, vol 592. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49283-3_11
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DOI: https://doi.org/10.1007/978-3-662-49283-3_11
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