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Privacy Leakage in Event-based Social Networks: A Meetup Case Study

Published:06 December 2017Publication History
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Abstract

Event-based social networks (EBSNs) are increasingly popular since they provide platforms on which online and offline activities are combined. Despite the increasing interest in EBSNs, little research has paid attention to the privacy issues coming from the unique features of EBSNs; the on-site information of users is highly relevant to real lives. In this paper, we try to investigate privacy leakages in Meetup, one of the most popular EBSN service. More specifically, we answer what private information can be inferred from the site's publicly available data. To this end, we conduct a measurement study by crawling webpages from Meetup containing 240K groups, 8.9M users, 27M group affiliations and 78M topical interests. By analyzing the dataset, we find that LGBT status of users, which is one of the most sensitive privacy information, can be predicted with 93% accuracy. Finally we discuss the cause of the privacy leakage on EBSNs and its possible ensuing damages.

References

  1. Lars Backstrom, Eric Sun, and Cameron Marlow. 2010. Find Me if You Can: Improving Geographical Prediction with Social and Spatial Proximity Proceedings of the World Wide Web (WWW'10). Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Gustavo E. A. P. A. Batista, Ronaldo C. Prati, and Maria Carolina Monard. 2004. A Study of the Behavior of Several Methods for Balancing Machine Learning Training Data. SIGKDD Explor. Newsl., Vol. 6, 1 (2004). Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Halil Bisgin, Nitin Agarwal, and Xiaowei Xu. 2010. Investigating Homophily in Online Social Networks. Proceedings of Web Intelligence and Intelligent Agent Technology (WIIAT). Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Shuo Chang, Vikas Kumar, Eric Gilbert, and Loren Terveen. 2014. Specialization, homophily, and gender in a social curation site: findings from pinterest Proceedings of the Computer Supported Cooperative Work and Social Computing. ACM, 674--686. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Zhiyuan Cheng, James Caverlee, and Kyumin Lee. 2010. You Are Where You Tweet: A Content-based Approach to Geo-locating Twitter Users Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM'10). Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Taejoong Chung, Jinyoung Han, Daejin Choi, Taekyoung "Ted" Kown, Huy Kang Kim, and Yanghee Choi. 2014. Unveiling Group Characteristics in Online Social Games: A Socio-Economic Analysis Proceedings of World Wide Web (WWW'14). Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. CNN. 2011. From Howard Dean to the tea party: The power of Meetup.com. http://edition.cnn.com/2011/11/07/tech/web/meetup-2012-campaign-sifry. (2011).Google ScholarGoogle Scholar
  8. Diego Couto, Gabriel Magno, Evandro Cunha, Marcos André Gonccalves, César Cambraia, and Virgilio Almeida. 2014. Noticing the Other Gender on Google, Proceedings of the ACM Web Science Conference, WebSci'14. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Justin Cranshaw, Eran Toch, Jason Hong, Aniket Kittur, and Norman Sadeh. 2010. Bridging the Gap Between Physical Location and Online Social Networks Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'10). Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Clodoveu Davis, Pappa L. Gisele, Diogo Renno Rocha de Oliveira, and Filipe de Lima Arcanjo. 2011. Inferring the Location of Twitter Messages Based on User Relationships. T. GIS, Vol. 15, 6 (2011), 735--751.Google ScholarGoogle ScholarCross RefCross Ref
  11. Ratan Dey, Cong Tang, Keith W. Ross, and Nitesh Saxena. 2012. Estimating age privacy leakage in online social networks Proceedings of the IEEE International Conference on Computer Communications (INFOCOM'12).Google ScholarGoogle Scholar
  12. Rong Du, Zhiwen Yu, Tao Mei, Zhitao Wang, Zhu Wang, and Bin Guo. 2014. Predicting Activity Attendance in Event-based Social Networks: Content, Context and Social Influence. In Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'14). Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Lise Getoor Elena Zheleva. 2009. To Join or Not to Join: The Illusion of Privacy in Social Networks with Mixed Public and Private User Profiles. In Proceedings of the World Wide Web (WWW'09). Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Andrew T. Fiore and Judith S. Donath. {n. d.}. Proceedings of Computer and Human Interaction (CHI).Google ScholarGoogle Scholar
  15. Jennifer Golbeck, Cristina Robles, Michon Edmondson, and Karen Turner. 2011. Predicting Personality from Twitter. In SocialCom/PASSAT. IEEE, 149--156.Google ScholarGoogle Scholar
  16. Scott A. Golder and Michael W. Macy. 2011. Diurnal and Seasonal Mood Vary with Work, Sleep, and Daylength Across Diverse Cultures. Science, Vol. 333, 6051 (Sept. 2011), 1878--1881.Google ScholarGoogle ScholarCross RefCross Ref
  17. G. Golub and W. Kahan. 1965. Calculating the singular values and pseudo-inverse of a matrix. SIAM J. Numer. Anal., Vol. 2, 2 (1965), 205--224.Google ScholarGoogle Scholar
  18. Australian Government. 2008. For Your Information: Australian Privacy Law and Practice (ALRC Report 108). http://www.alrc.gov.au/publications/report-108A. (2008).Google ScholarGoogle Scholar
  19. Shion Guha and Stephen B Wicker. 2015. Do Birds of a Feather Watch Each Other?: Homophily and Social Surveillance in Location Based Social Networks. In Proceedings of the Computer Supported Cooperative Work and Social Computing. ACM, 1010--1020. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Junwei Han, Jianwei Niu, Alvin Chin, Wei Wang, Chao Tong, and Xia Wang. 2012. How Online Social Network Affects Offline Events: A Case Study on Douban UIC/ATC. 752--757. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Haibo He and Edwardo A. Garcia. 2009. Learning from Imbalanced Data. IEEE Trans. on Knowl. and Data Eng. Vol. 21, 9 (Sept. 2009).Google ScholarGoogle Scholar
  22. Brent Hecht, Lichan Hong, Bongwon Suh, and Ed H. Chi. 2011. Tweets from Justin Bieber's Heart: The Dynamics of the Location Field in User Profiles Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI'11). Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Hughes, David John, Rowe, Moss, Batey, Mark, Lee, and Andrew. 2012. A tale of two sites: Twitter vs. Facebook and the personality predictors of social media usage. Computers in Human Behavior Vol. 28, 2 (2012), 561--569. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Carter Jernigan and Behram F. T. Mistree. 2009. Gaydar: Facebook Friendships Expose Sexual Orientation. First Monday, Vol. 14, 10 (2009).Google ScholarGoogle Scholar
  25. Kenji Kira and Larry A. Rendell. 1992. A Practical Approach to Feature Selection. In Proceedings of the Ninth International Workshop on Machine Learning (ML92). 249--256. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Michal Kosinski, David Stillwell, and Thore Graepel. 2013. Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences, Vol. 110, 15 (April. 2013), 5802--5805.Google ScholarGoogle ScholarCross RefCross Ref
  27. Haewoon Kwak and et al. 2010. What is Twitter, a social network or a news media? Proceedings of the World Wide Web (WWW'10). Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Ellen Lewin and William L. Leap. 2002. Studying Lesbian and Gay Languages: Vocabulary, Text-making, and Beyond.Google ScholarGoogle Scholar
  29. Sue Ellen Linville. 1998. Acoustic Correlates of Perceived versus Actual Sexual Orientation in Men's Speech. Folia Phoniatr Logop Vol. 50 (1998), 35--48.Google ScholarGoogle ScholarCross RefCross Ref
  30. Xingjie Liu, Qi He, Yuanyuan Tian, Wang-Chien Lee, John McPherson, and Jiawei Han. 2012. Event-based Social Networks: Linking the Online and Offline Social Worlds Proceedings of the ACM International Conference on Knowledge Discovery and Data Mining (KDD'12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Sai Lu, Janne Lindqvist, and Rebecca N. Wright. 2014. Uncovering Facebook Side Channels and User Attitudes Proceedings of Web 2.0 Security and Privacy Workshop (W2SP). IEEE.Google ScholarGoogle Scholar
  32. Jalal Mahmud, Jeffrey Nichols, and Clemens Drews. 2014. Home Location Identification of Twitter Users. ACM Transactions on Intelligent Systems and Technology, Vol. 5, 3 (2014). Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Huina Mao, Xin Shuai, and Apu Kapadia. 2011. Loose Tweets: An Analysis of Privacy Leaks on Twitter Proceedings of the ACM workshop on Privacy in the electronic society (WEPS'11). Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Miller McPherson, Lynn Smith-Lovin, and James M. Cook. 2001. Birds of a Feather: Homophily in Social Networks. Annual Review of Sociology Vol. 27 (2001), 415--444.Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Meetup.com. 2015. About Meetup. http://www.meetup.com/about/. (2015).Google ScholarGoogle Scholar
  36. Jimmy Lin Michael D. Lieberman. 2012. You Are Where You Edit: Locating Wikipedia Contributors through Edit Histories Proceedings of the International AAAI Conference on Web and Social Media (ICWSM'10).Google ScholarGoogle Scholar
  37. Alan Mislove, Bimal Viswanath, Krishna P. Gummadi, and Peter Druschel. 2010. You are who you know: inferring user profiles in online social networks Proceedings of Web search and data mining (WSDM). Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Benjamin Munson. 2007. The Acoustic Correlates of Perceived Masculinity, Perceived Femininity, and Perceived Sexual Orientation. Language and Speech Vol. 50 (2007), 125--142.Google ScholarGoogle ScholarCross RefCross Ref
  39. Tatiana Pontes, Marisa Vasconcelos, Jussara Almeida, Ponnurangam Kumaraguru, and Virgilio Almeida. 2012. We Know Where You Live: Privacy Characterization of Foursquare Behavior Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Adrian Popescu and Gregory Grefenstette. 2010. Mining user home location and gender from flickr tags Proceedings of the International AAAI Conference on Web and Social Media (ICWSM'10).Google ScholarGoogle Scholar
  41. Huffington Post. 2014. Meetup.com: A Secret Weapon for Your Career and Personal Brand. http://www.huffingtonpost.com/stephan-spencer/using-meetupcom-as-a-bran_b_4767898.html. (2014).Google ScholarGoogle Scholar
  42. Zhi Qiao, Peng Zhang, Chuan Zhou, Yanan Cao, Li Guo, and Yanchuan Zhang. 2014. Event Recommendation in Event-Based Social Networks Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI'14). Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. D. Quercia, M. Kosinski, D. Stillwell, and J. Crowcroft. 2011. Our Twitter Profiles, Our Selves: Predicting Personality with Twitter Proceedings of the Third International Conference on Social Computing (SocialCom) and the Third International Conference on Privacy, Security, Risk and Trust (PASSAT). IEEE, 180--185.Google ScholarGoogle Scholar
  44. Norman M. Sadeh, Jason I. Hong, Lorrie Faith Cranor, Ian Fette, Patrick Gage Kelley, Madhu K. Prabaker, and Jinghai Rao. 2009. Understanding and capturing people's privacy policies in a mobile social networking application. Personal and Ubiquitous Computing Vol. 13, 6 (2009), 401--412. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Thomas H. Sander. 2005. E-associations: using technology to connect citizens: the case of meetup.com. American Political Science Association (2005), 47.Google ScholarGoogle Scholar
  46. Lauren F. Sessions. 2010. How offline gatherings affect online communities -- When virtual community members meetup. Information, Communication & Society Vol. 13, 3 (2010).Google ScholarGoogle Scholar
  47. Jan Skopek, Florian Schulz, and Hans-Peter Blossfeld. 2010. Who Contacts Whom? Educational Homophily in Online Mate Selection. European Sociological Review Vol. 27, 2 (2010), 180--195.Google ScholarGoogle ScholarCross RefCross Ref
  48. B. Tarbush and A. Teytelboym. 2012. Homophily in Online Social Networks. Proceedings of International Workshop on Internet and Network Economics Vol. 7695 (2012), 512--518. Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. Yla R. Tausczik and James W. Pennebaker. 2010. The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods. http://homepage.psy.utexas.edu/homepage/students/Tausczik/Yla/index.html. (2010).Google ScholarGoogle Scholar
  50. Andranik Tumasjan, Timm Sprenger, Philipp Sandner, and Isabell Welpe. 2010. Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment Proceedings of the International AAAI Conference on Weblogs and Social Media (ICWSM'10).Google ScholarGoogle Scholar
  51. Human Rights Library University of Minnesota. 2013. Study guide, Sexual Orientation and Human Rights. http://hrlibrary.umn.edu/edumat/studyguides/sexualorientation.html. (2013).Google ScholarGoogle Scholar
  52. Claudia Wagner, Sitaram Asur, and Joshua M. Hailpern. 2013. Religious Politicians and Creative Photographers: Automatic User Categorization in Twitter. International Conference on Social Computing (SocialCom'13). 303--310. Google ScholarGoogle ScholarDigital LibraryDigital Library
  53. Shaomei Wu, Chenhao Tan, Jon Kleinberg, and Michael Macy. 2011. Does Bad News Go Away Faster?. In Proceedings of the International AAAI Conference on Weblogs and Social Media (ICWSM'11).Google ScholarGoogle Scholar
  54. Bin Xu, Alvin Chin, and Dan Cosley. 2013. On How Event Size and Interactivity Affect Social Networks Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI'13). Google ScholarGoogle ScholarDigital LibraryDigital Library

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