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Forum-Oriented Research on Water Army Detection for Bursty Topics

机译:面向论坛的水军突发事件检测研究

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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.
机译:水军是指一群特殊的在线用户,他们因在隐藏的不同目的在不同的在线社区和网站上发布评论和新主题或文章而获得报酬。由于水军派遣行为的性质尚未完全理解,对网络论坛突发性话题的动力检测仍然是一个难以解决的问题。通过对突发性话题演变和水军的发帖行为进行分析,发现水军主导的话题在潜伏期表现出与一般话题不同的特征。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性主题分类算法,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。

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