Research on Users Associated Technology across Social Network

doi:10.3969/j.issn.1671-1122.2017.02.008

Abstract

Abstract:

With the massive popularity of social networks in recent years, social network has played a very important role in people’s daily lives. It has a lot of users, but few of them needs real name authentication, which malicious users can freely spread rumors and bad information to the public and bring challenges to Internet regulations. Therefore, associating entity users across different social networks, establish the network identification can help identify and supervise the users. The paper’s main research work are as follows. Firstly we designed a system to collect QZone and Weibo’s user’s information. Secondly we analyze the data we collect from the internet which contains 5,440,000 users of Weibo and 24,590,000 users of QZone. Then we proposed a model of users associated across social network. This model is based on logic regression model which is used to classify the users, at the same time, according to the principle of SimRank algorithm, the SNC algorithm is proposed to eliminate the noise and improve the accuracy of the model. Finally we use the model on the dataset we collected. The experimental result shows that the model can filter out pairs of users that associated strongly, the accuracy of the model has improved and the model can associate users of different social networks after pruning.

Key words: cross social networks, users association, information collection, SNC algorithm, logistic regression

CLC Number:

TP309

Liang LUO, Wenxian WANG, Jie ZHONG, Haizhou WANG. Research on Users Associated Technology across Social Network[J]. Netinfo Security, 2017, 17(2): 51-58.

Figures/Tables 12

References 21

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