Title :
Forum-Oriented Research on Water Army Detection for Bursty Topics
Author :
Huijie Xu ; Wandong Cai ; Guirong Chen
Author_Institution :
Sch. of Comput. Sci. & Technol., Northwestern Polytech. Univ., Xi´an, China
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.
Keywords :
Web sites; learning (artificial intelligence); pattern classification; support vector machines; text analysis; SVM active learning; SVM-based classification decision issue; Web forum; Websites; bursty topic classification algorithm; driving force detection; forum-oriented research; hidden purposes; latency stage; online communities; online users; water army detection; Accuracy; Algorithm design and analysis; Classification algorithms; Indexes; Support vector machines; Training; Water; active learning; bursty topic; water army detection; web forum;
Conference_Titel :
Networking, Architecture, and Storage (NAS), 2014 9th IEEE International Conference on
Conference_Location :
Tianjin
DOI :
10.1109/NAS.2014.18
