skip to main content
research-article

Understanding Cross-Site Linking in Online Social Networks

Authors Info & Claims
Published:27 September 2018Publication History
Skip Abstract Section

Abstract

As a result of the blooming of online social networks (OSNs), a user often holds accounts on multiple sites. In this article, we study the emerging “cross-site linking” function available on mainstream OSN services including Foursquare, Quora, and Pinterest. We first conduct a data-driven analysis on crawled profiles and social connections of all 61.39 million Foursquare users to obtain a thorough understanding of this function. Our analysis has shown that the cross-site linking function is adopted by 57.10% of all Foursquare users, and the users who have enabled this function are more active than others. We also find that the enablement of cross-site linking might lead to privacy risks. Based on cross-site links between Foursquare and external OSN sites, we formulate cross-site information aggregation as a problem that uses cross-site links to stitch together site-local information fields for OSN users. Using large datasets collected from Foursquare, Facebook, and Twitter, we demonstrate the usefulness and the challenges of cross-site information aggregation. In addition to the measurements, we carry out a survey collecting detailed user feedback on cross-site linking. This survey studies why people choose to or not to enable cross-site linking, as well as the motivation and concerns of enabling this function.

References

  1. Fabian Abel, Samur Araújo, Qi Gao, and Geert-Jan Houben. 2011. Analyzing cross-system user modeling on the social web. In Proceedings of the International Conference on Web Engineering (ICWE’11). Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Jacopo A. Baggio, Shauna B. BurnSilver, Alex Arenas, James S. Magdanz, Gary P. Kofinas, and Manlio De Domenico. 2016. Multiplex social ecological network analysis reveals how social changes affect community robustness more than resource depletion. Proceedings of the National Academy of Sciences 113, 48 (2016), 13708--13713.Google ScholarGoogle ScholarCross RefCross Ref
  3. Leo Breiman. 2001. Random forests. Machine Learning 45, 1 (2001), 5--32. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Qiang Cao, Michael Sirivianos, Xiaowei Yang, and Tiago Pregueiro. 2012. Aiding the detection of fake accounts in large scale social online services. In Proceedings of the USENIX Symposium on Networked Systems Design and Implementation (NSDI'12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Xuezhi Cao and Yong Yu. 2016. BASS: A bootstrapping approach for aligning heterogenous social networks. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Tianqi Chen and Carlos Guestrin. 2016. XGBoost: A scalable tree boosting system. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16). Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Terence Chen, Mohamed Ali Kaafar, and Roksana Boreli. 2013. The where and when of finding new friends: Analysis of a location-based social discovery networks. In Proceedings of the International Conference on Weblogs and Social Media (ICWSM'13).Google ScholarGoogle Scholar
  8. Terence Chen, Mohamed Ali Kaafar, Arik Friedman, and Roksana Boreli. 2012. Is more always merrier? A deep dive into online social footprints. In Proceedings of the ACM Workshop on Online Social Networks (WOSN'12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Yang Chen, Jiyao Hu, Hao Zhao, Yu Xiao, and Pan Hui. 2018. Measurement and analysis of the swarm social network with tens of millions of nodes. IEEE Access 6 (2018), 4547--4559.Google ScholarGoogle ScholarCross RefCross Ref
  10. Manlio De Domenico, Albert Solé-Ribalta, Emanuele Cozzo, Mikko Kivelä, Yamir Moreno, Mason A. Porter, Sergio Gómez, and Alex Arenas. 2013. Mathematical formulation of multilayer networks. Physical Review X 3, 4 (Dec. 2013), 041022.Google ScholarGoogle Scholar
  11. Cong Ding, Yang Chen, and Xiaoming Fu. 2013. Crowd crawling: Towards collaborative data collection for large-scale online social networks. In Proceedings of the ACM Conference on Online Social Networks (COSN'13). Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, and Chih-Jen Lin. 2008. LIBLINEAR: A library for large linear classification. Journal of Machine Learning Research 9 (2008), 1871--1874. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Reza Farahbakhsh, Ángel Cuevas, and Noël Crespi. 2016. Characterization of cross-posting activity for professional users across Facebook, Twitter and Google+. Social Network Analysis and Mining 6, 1 (2016), 33:1--33:14.Google ScholarGoogle Scholar
  14. Aleksandr Farseev and Tat-Seng Chua. 2017. Tweetfit: Fusing multiple social media and sensor data for wellness profile learning. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI'17).Google ScholarGoogle Scholar
  15. Aleksandr Farseev, Liqiang Nie, Mohammad Akbari, and Tat-Seng Chua. 2015. Harvesting multiple sources for user profile learning: A big data study. In Proceedings of the International Conference on Multimedia Retrieval (ICMR'15). Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Tom Fawcett. 2006. An introduction to ROC analysis. Pattern Recognition Letters 27, 8 (2006), 861--874. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Maksym Gabielkov, Ashwin Rao, and Arnaud Legout. 2014. Studying social networks at scale: Macroscopic anatomy of the Twitter social graph. In Proceedings of the ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS'14). Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Oana Goga, Gerald Friedland, Howard Lei, Robin Sommer, Sree Hari Krishnan, and Renata Teixeira. 2013. Exploiting innocuous activity for correlating users across sites. In Proceedings of the World Wide Web Conference (WWW'13). Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Neil Zhenqiang Gong, Wenchang Xu, Ling Huang, Prateek Mittal, Emil Stefanov, Vyas Sekar, and Dawn Song. 2012. Evolution of social-attribute networks: Measurements, modeling, and implications using Google+. In Proceedings of the ACM Internet Measurement Conference (IMC'12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Qingyuan Gong, Yang Chen, Xinlei He, Zhou Zhuang, Tianyi Wang, Hong Huang, Xin Wang, and Xiaoming Fu. 2018. DeepScan: Exploiting deep learning for malicious account detection in location-based social networks. IEEE Communications Magazine (2018). (In press).Google ScholarGoogle Scholar
  21. Wanqiu Guan, Haoyu Gao, Mingmin Yang, Yuan Li, Haixin Ma, Weining Qian, Zhigang Cao, and Xiaoguang Yang. 2014. Analyzing user behavior of the micro-blogging website Sina Weibo during hot social events. Physica A: Statistical Mechanics and Its Applications 395, 0 (2014), 340--351.Google ScholarGoogle ScholarCross RefCross Ref
  22. Jinyoung Han, Daejin Choi, Byung-Gon Chun, Ted Kwon, Hyun-chul Kim, and Yanghee Choi. 2014. Collecting, organizing, and sharing pins in Pinterest: Interest-driven or social-driven? In Proceedings of the ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS'14). Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Tianran Hu, Eric Bigelow, Jiebo Luo, and Henry Kautz. 2017. Tales of two cities: Using social media to understand idiosyncratic lifestyles in distinctive metropolitan areas. IEEE Transactions on Big Data 3, 1 (2017), 55--66.Google ScholarGoogle ScholarCross RefCross Ref
  24. Danesh Irani, Steve Webb, Kang Li, and Calton Pu. 2011. Modeling unintended personal-information leakage from multiple online social networks. IEEE Internet Computing 15, 3 (2011), 13--19. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Paridhi Jain, Ponnurangam Kumaraguru, and Anupam Joshi. 2016. Other times, other values: Leveraging attribute history to link user profiles across online social networks. Social Network Analysis and Mining 6, 1 (2016), 85.Google ScholarGoogle ScholarCross RefCross Ref
  26. Long Jin, Yang Chen, Tianyi Wang, Pan Hui, and Athanasios V. Vasilakos. 2013. Understanding user behavior in online social networks: A survey. IEEE Communications Magazine 51, 9 (2013), 144--150.Google ScholarGoogle ScholarCross RefCross Ref
  27. Xiangnan Kong, Jiawei Zhang, and Philip S. Yu. 2013. Inferring anchor links across multiple heterogeneous social networks. In Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM'13). Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Juhi Kulshrestha, Farshad Kooti, Ashkan Nikravesh, and Krishna P. Gummadi. 2012. Geographic dissection of the Twitter network. In Proceedings of the International Conference on Weblogs and Social Media (ICWSM'12).Google ScholarGoogle Scholar
  29. Haewoon Kwak, Changhyun Lee, Hosung Park, and Sue Moon. 2010. What is Twitter, a social network or a news media? In Proceedings of the World Wide Web Conference (WWW'10). Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Roy Ka-Wei Lee, Tuan-Anh Hoang, and Ee-Peng Lim. 2017. On analyzing user topic-specific platform preferences across multiple social media sites. In Proceedings of the World Wide Web Conference (WWW'17). Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Shihan Lin, Rong Xie, Qinge Xie, Hao Zhao, and Yang Chen. 2017. Understanding user activity patterns of the swarm app: A data-driven study. In Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers (UbiComp/ISWC'17). Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Siyuan Liu, Shuhui Wang, Feida Zhu, Jinbo Zhang, and Ramayya Krishnan. 2014. HYDRA: Large-scale social identity linkage via heterogeneous behavior modeling. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD'14). Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. John Maheswaran, Daniel Jackowitz, Ennan Zhai, David Isaac Wolinsky, and Bryan Ford. 2016. Building privacy-preserving cryptographic credentials from federated online identities. In Proceedings of the ACM Conference on Data and Application Security and Privacy (CODASPY'16). Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Quinn McNemar. 1947. Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika 12, 2 (1947), 153--157.Google ScholarGoogle ScholarCross RefCross Ref
  35. Pasquale De Meo, Emilio Ferrara, Fabian Abel, Lora Aroyo, and Geert-Jan Houben. 2013. Analyzing user behavior across social sharing environments. ACM Transactions on Intelligent Systems and Technology 5, 1 (2013), 14:1--14:31. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Tehila Minkus, Kelvin Liu, and Keith W. Ross. 2015. Children seen but not heard: When parents compromise children’s online privacy. In Proceedings of the World Wide Web Conference (WWW'15). Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Dung T. Nguyen, Huiyuan Zhang, Soham Das, My T. Thai, and Thang N. Dinh. 2013. Least cost influence in multiplex social networks: Model representation and analysis. In Proceedings of the IEEE International Conference on Data Mining (ICDM'13).Google ScholarGoogle Scholar
  38. Anastasios Noulas, Salvatore Scellato, Cecilia Mascolo, and Massimiliano Pontil. 2011. An empirical study of geographic user activity patterns in foursquare. In Proceedings of the International Conference on Weblogs and Social Media (ICWSM'11).Google ScholarGoogle Scholar
  39. Neil O’Hare and Vanessa Murdock. 2012. Gender-based models of location from flickr. In Proceedings of the ACM Workshop on Geotagging and Its Applications in Multimedia (GeoMM'12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Raphael Ottoni, Diego de Las Casas, João Paulo Pesce, Wagner Meira Jr., Christo Wilson, Alan Mislove, and Virgílio Almeida. 2014. Of pins and tweets: Investigating how users behave across image- and text-based social networks. In Proceedings of the International Conference on Weblogs and Social Media (ICWSM'14).Google ScholarGoogle Scholar
  41. Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd. 1999. The Pagerank citation ranking: Bringing order to the web. Stanford InfoLab.Google ScholarGoogle Scholar
  42. Daniel Preoţiuc-Pietro and Trevor Cohn. 2013. Mining user behaviours: A study of check-in patterns in location based social networks. In Proceedings of the ACM Web Science Conference (WebSci'13). Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Daniele Quercia, Mansoureh Bodaghi, and Jon Crowcroft. 2012. Loosing “friends” on facebook. In Proceedings of the ACM Web Science Conference (WebSci'12).Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. J. Ross Quinlan. 1993. C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Francisco. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Salvatore Scellato, Anastasios Noulas, Renaud Lambiotte, and Cecilia Mascolo. 2011. Socio-spatial properties of online location-based social networks. In Proceedings of the International Conference on Weblogs and Social Media (ICWSM'11).Google ScholarGoogle Scholar
  46. Thiago H. Silva, Pedro O. S. Vaz de Melo, Jussara M. Almeida, Juliana Salles, and Antonio A. F. Loureiro. 2014. Revealing the city that we cannot see. ACM Transactions on Internet Technology 14, 4 (Dec. 2014), 26:1--26:23. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Xiaodan Song, Yun Chi, Koji Hino, and Belle Tseng. 2007. Identifying opinion leaders in the blogosphere. In Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM'07). Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. Jie Tang, Tiancheng Lou, and Jon Kleinberg. 2012. Inferring social ties across heterogenous networks. In Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM'12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. Shiliang Tang, Xinyi Zhang, Jenna Cryan, Miriam J. Metzger, Haitao Zheng, and Ben Y. Zhao. 2017. Gender bias in the job market: A longitudinal analysis. Proceedings of the ACM on Human-Computer Interaction 1, CSCW, Article 99 (Dec. 2017), 19 pages. Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Mike Thelwall. 2008. Social networks, gender and friending: An analysis of MySpace member profiles. Journal of the American Society for Information Science and Technology 59, 8 (2008), 1321--1330. Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. Asimina Vasalou, Adam N. Joinson, and Delphine Courvoisier. 2010. Cultural differences, experience with social networks and the nature of “true commitment” in Facebook. International Journal of Human-Computer Studies 68, 10 (2010), 719--728. Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. Marisa Affonso Vasconcelos, Saulo Ricci, Jussara Almeida, Fabrício Benevenuto, and Virgílio Almeida. 2012. Tips, dones and to-dos: Uncovering user profiles in foursquare. In Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM'12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  53. Giridhari Venkatadri, Oana Goga, Changtao Zhong, Bimal Viswanath, Krishna P. Gummadi, and Nishanth Sastry. 2016. Strengthening weak identities through inter-domain trust transfer. In Proceedings of the World Wide Web Conference (WWW'16). Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. King wa Fu and Michael Chau. 2013. Reality check for the Chinese microblog space: A random sampling approach. PLoS ONE 8, 3 (2013), e58356.Google ScholarGoogle ScholarCross RefCross Ref
  55. Gang Wang, Konark Gill, Manish Mohanlal, Haitao Zheng, and Ben Y. Zhao. 2013. Wisdom in the social crowd: An analysis of quora. In Proceedings of the World Wide Web Conference (WWW'13). Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. Gang Wang, Sarita Y. Schoenebeck, Haitao Zheng, and Ben Y. Zhao. 2016. “Will check-in for badges”: Understanding bias and misbehavior on location-based social networks. In Proceedings of the International Conference on Weblogs and Social Media (ICWSM'16).Google ScholarGoogle Scholar
  57. Huijuan Wang, Qian Li, G. D’Agostino, Shlomo Havlin, H. Stanley, and Piet Van Mieghem. 2013. Effect of the interconnected network structure on the epidemic threshold. Physical Review E 88, 2 (2013), 022801.Google ScholarGoogle ScholarCross RefCross Ref
  58. Pinghui Wang, Wenbo He, and Junzhou Zhao. 2014. A tale of three social networks: User activity comparisons across Facebook, Twitter, and Foursquare. IEEE Internet Computing 18, 2 (2014), 10--15.Google ScholarGoogle ScholarCross RefCross Ref
  59. Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan, and Amit P. Sheth. 2014. Cursing in english on Twitter. In Proceedings of the ACM Conference on Computer Supported Cooperative Work 8 Social Computing (CSCW'14). Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. Yi-Chia Wang, Moira Burke, and Robert E. Kraut. 2013. Gender, topic, and audience response: An analysis of user-generated content on Facebook. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI'13). Google ScholarGoogle ScholarDigital LibraryDigital Library
  61. Jianshu Weng, Ee-Peng Lim, Jing Jiang, and Qi He. 2010. TwitterRank: Finding topic-sensitive influential Twitterers. In Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM'10). Google ScholarGoogle ScholarDigital LibraryDigital Library
  62. Christo Wilson, Bryce Boe, Alessandra Sala, Krishna P. N. Puttaswamy, and Ben Y. Zhao. 2009. User interactions in social networks and their implications. In Proceedings of the ACM European Conference on Computer Systems (EuroSys'09). Google ScholarGoogle ScholarDigital LibraryDigital Library
  63. Chunjing Xiao, Ling Su, Juan Bi, Yuxia Xue, and Aleksandar Kuzmanovic. 2012. Selective behavior in online social networks. In Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  64. Dingqi Yang, Daqing Zhang, Bingqing Qu, and Philippe Cudré-Mauroux. 2016. PrivCheck: Privacy-preserving check-in data publishing for personalized location based services. In Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'16). Google ScholarGoogle ScholarDigital LibraryDigital Library
  65. Yiming Yang and Jan O. Pedersen. 1997. A comparative study on feature selection in text categorization. In Proceedings of the International Conference on Machine Learning (ICML'97). Google ScholarGoogle ScholarDigital LibraryDigital Library
  66. Zhi Yang, Christo Wilson, Xiao Wang, Tingting Gao, Ben Y. Zhao, and Yafei Dai. 2014. Uncovering social network sybils in the wild. ACM Transactions on Knowledge Discovery from Data 8, 1 (2014), 2:1--2:29. Google ScholarGoogle ScholarDigital LibraryDigital Library
  67. Nicholas Jing Yuan, Fuzheng Zhang, Defu Lian, Kai Zheng, Siyu Yu, and Xing Xie. 2013. We know how you live: Exploring the spectrum of urban lifestyles. In Proceedings of the ACM Conference on Online Social Networks (COSN'13). Google ScholarGoogle ScholarDigital LibraryDigital Library
  68. Changtao Zhong, Hau-wen Chang, Dmytro Karamshuk, Dongwon Lee, and Nishanth Sastry. 2017. Wearing many (social) hats: How different are your different social network personae? In Proceedings of the International Conference on Weblogs and Social Media (ICWSM'17).Google ScholarGoogle Scholar
  69. Changtao Zhong, Nicolas Kourtellis, and Nishanth Sastry. 2016. Pinning alone? A study of the role of social ties on Pinterest. In Proceedings of the International Conference on Weblogs and Social Media (ICWSM'16).Google ScholarGoogle Scholar
  70. Changtao Zhong, Mostafa Salehi, Sunil Shah, Marius Cobzarenco, Nishanth Sastry, and Meeyoung Cha. 2014. Social bootstrapping: How Pinterest and last.fm social communities benefit by borrowing links from Facebook. In Proceedings of the World Wide Web Conference (WWW'14). Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Understanding Cross-Site Linking in Online Social Networks

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image ACM Transactions on the Web
        ACM Transactions on the Web  Volume 12, Issue 4
        November 2018
        215 pages
        ISSN:1559-1131
        EISSN:1559-114X
        DOI:10.1145/3281744
        Issue’s Table of Contents

        Copyright © 2018 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 27 September 2018
        • Revised: 1 March 2018
        • Accepted: 1 March 2018
        • Received: 1 July 2017
        Published in tweb Volume 12, Issue 4

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Research
        • Refereed

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader