Forum-Oriented Research on Water Army Detection for Bursty Topics

Huijie Xu, Wandong Cai, Guirong Chen
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引用次数: 1

Abstract

Water army means a special group of online users who get paid for posting comments and new threads or articles on different online communities and websites for some hidden purposes. Due to the fact that the nature of the posting behavior of water army is not fully and understood, the driving force detection of the bursty topic for web forum is still a difficult problem to solve. According to the analysis of bursty topics evolution and the posting behavior of water army, it is found that the topics driven by water army exhibit the characteristics different from general topics in their latency stage. Based on this discovery, the paper proposes a novel bursty topic classification algorithm, based on SVM active learning, which transforms the water army detection issue to a SVM-based classification decision issue. The experimental results show that the proposed algorithm has higher detection accuracy and detection efficiency.
面向论坛的突发性话题水军检测研究
水军指的是一群特殊的网络用户,他们为了某些不可告人的目的,在不同的网络社区和网站上发表评论、新帖子或文章,从而获得报酬。由于对水军发帖行为的性质不完全了解,网络论坛突发话题的驱动力检测仍然是一个难以解决的问题。通过对突发话题演化和水军发布行为的分析,发现由水军驱动的话题在潜伏期表现出不同于一般话题的特征。基于这一发现,本文提出了一种基于支持向量机主动学习的突发主题分类算法,将水军检测问题转化为基于支持向量机的分类决策问题。实验结果表明,该算法具有较高的检测精度和检测效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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