Detection of Zombie Followers in SINA Weibo

被引:0
|
作者
Zhang, Zhedi [1 ]
Zou, Futai [1 ]
Pan, Li [1 ]
Pei, Bei [2 ]
Li, Jianhua [1 ]
机构
[1] Shanghai Jiao Tong Univ, Coll Informat Secur, Shanghai, Peoples R China
[2] Minist Publ Secur, Key Lab Informat Network Secur, Shanghai, Peoples R China
关键词
zombie followers; feature analyze; web spider; user behavior; machine learning;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
SINA Weibo is one of the most popular social networks in China where people can share everything in the form of pictures, texts, videos or links. The prime motivation pushing people to post tweet is to increase their number of followers. However, some artificial followers that can be bought and sold online, called zombie followers, emerge in endlessly. This paper introduces a series of algorithms to detect the zombie followers efficiently and accurately by analyzing two kinds of users' features. Firstly distinguish the zombie followers out of the legitimate users manually, and then utilize SVM machine learning classifier to detect the zombie followers automatically. Finally, through the estimation on the real dataset, the zombie followers can be correctly detected out of the legitimate users at high accuracy (99.78%) and the false positive rate is 11.57%.
引用
收藏
页码:2476 / 2480
页数:5
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