Deciphering privacy leakage in microblogging social networks: a measurement study

Privacy leakage has become a growing concern for microblogging social networks. While the use of social networks facilitates information sharing and collaboration, many users are disclosing their sensitive information in the meanwhile. In this paper, we aim to better understand privacy leakage in the microblogging social networks. Towards this, we conducted a comprehensive measurement study to investigate the privacy problem in the largest microblogging social network in China from macroscopic, medium-scopic, and microscopic perspectives. For the macroscopic analysis, we analyzed the profile pages of 1.57 million users and obtained a broad picture on the openness of users and the leakage of user-sensitive information via their profile pages. We find that verified users prefer to disclose more information on their profile pages than unverified users, and the youth and singles normally have a higher open degree. For the medium-scopic analysis, we investigated the social links among Weibo users and show the feasibility to identify the closest friends of a user. For the microscopic analysis, we explored in-depth a small set of users by textual analysis and manual analysis. We observe that unverified users leak slightly more privacy than verified users, and males are only a bit more open than females. We can further identify the location, age, and daily activities of a user by manually analyzing their public information on the Weibo. In addition to providing insight into the severity of privacy leakage, we also discuss a few possible solutions to protect user privacy in the microblogging social networks. Copyright © 2015John Wiley & Sons, Ltd.

[1]  Tao Qin,et al.  Who are active? An in-depth measurement on user activity characteristics in sina microblogging , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[2]  Keith W. Ross,et al.  Estimating age privacy leakage in online social networks , 2012, 2012 Proceedings IEEE INFOCOM.

[3]  Balachander Krishnamurthy,et al.  On the leakage of personally identifiable information via online social networks , 2009, CCRV.

[4]  Daniele Quercia,et al.  Our Twitter Profiles, Our Selves: Predicting Personality with Twitter , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.

[5]  Balachander Krishnamurthy,et al.  For sale : your data: by : you , 2011, HotNets-X.

[6]  Matthew Richardson,et al.  Yes, there is a correlation: - from social networks to personal behavior on the web , 2008, WWW.

[7]  Sandra Servia Rodríguez,et al.  Inferring Contexts From Facebook Interactions: A Social Publicity Scenario , 2013, IEEE Transactions on Multimedia.

[8]  Saikat Guha,et al.  NOYB: privacy in online social networks , 2008, WOSN '08.

[9]  Christo Wilson,et al.  Tweeting under pressure: analyzing trending topics and evolving word choice on sina weibo , 2013, COSN '13.

[10]  Tian Jie,et al.  A Research on Famous-User Network of SINA-Weibo , 2012, 2012 Second International Conference on Instrumentation, Measurement, Computer, Communication and Control.

[11]  Yong Zhang,et al.  User influence analysis on micro blog , 2012, 2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems.