基于人工免疫危险理论的微博水军用户检测研究

doi:10.11896／j.issn.1002-137X.2018.11.020

Abstract

Abstract: This paper introduced the danger theory in artificial immunity system into the analysis of user behavior cha-racteristics to identify the spammers in Weibo effectively.Taking Sina Weibo as an example,this paper analyzed the behavior characteristics of Weibo spammers,selected the total number of Weibo,Weibo level,user authentication,sunshine credit and the number of fans as attribute characteristics and used the analysis results of attribute characteristics as the characteristic signals of distinguishing the spammers and the normal users.After that,the recognition of Sina Weibo spammers can be achieved based on Dendritic Cells Algorithm.The real data of Sina Weibo users was used to verify the effectiveness of the proposed algorithm and conducted comparison experiments.The experimental results suggest that this algorithm can effectively detect the spammers in Sina Weibo and has high detection accuracy.

Key words: Artificial immunity, Behavioral characteristics, Danger theory, Dendritic cells algorithm, Weibo spammers

CLC Number:

TP393

YANG Chao, QIN Ting-dong, FAN Bo, LI Tao. Study on Detection of Weibo Spammers Based on Danger Theory in Artificial Immunity System[J].Computer Science, 2018, 45(11): 138-142.

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https://www.jsjkx.com/EN/Y2018/V45/I11/138

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