Connecting users across social media sites: A behavioral-modeling approach

Reza Zafarani; Huan Liu

doi:10.1145/2487575.2487648

Connecting users across social media sites: A behavioral-modeling approach

Reza Zafarani, Huan Liu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

330 Scopus citations

Abstract

People use various social media for different purposes. The information on an individual site is often incomplete. When sources of complementary information are integrated, a better profile of a user can be built to improve online services such as verifying online information. To integrate these sources of information, it is necessary to identify individuals across social media sites. This paper aims to address the cross-media user identification problem. We introduce a methodology (MOBIUS) forfinding a mapping among identities of individuals across social media sites. It consists of three key components: The first component identifies users' unique behavioral patterns that lead to information redundancies across sites; the second component constructs features that exploit information redundancies due to these behavioral patterns; and the third component employs machine learning for effective user identification. We formally define the cross-media user identification problem and show that MOBIUS is effective in identifying users across social media sites. This study paves the way for analysis and mining across social media sites, and facilitates the creation of novel online services across sites.

Original language	English (US)
Title of host publication	KDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Editors	Rajesh Parekh, Jingrui He, Dhillon S. Inderjit, Paul Bradley, Yehuda Koren, Rayid Ghani, Ted E. Senator, Robert L. Grossman, Ramasamy Uthurusamy
Publisher	Association for Computing Machinery
Pages	41-49
Number of pages	9
ISBN (Electronic)	9781450321747
DOIs	https://doi.org/10.1145/2487575.2487648
State	Published - Aug 11 2013
Event	19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013 - Chicago, United States Duration: Aug 11 2013 → Aug 14 2013

Publication series

Name	Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Volume	Part F128815

Other

Other	19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013
Country/Territory	United States
City	Chicago
Period	8/11/13 → 8/14/13

Keywords

Cross-media analysis
MOBIUS
User identification

ASJC Scopus subject areas

Software
Information Systems

Access to Document

10.1145/2487575.2487648

Cite this

Zafarani, R., & Liu, H. (2013). Connecting users across social media sites: A behavioral-modeling approach. In R. Parekh, J. He, D. S. Inderjit, P. Bradley, Y. Koren, R. Ghani, T. E. Senator, R. L. Grossman, & R. Uthurusamy (Eds.), KDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 41-49). Article 2487648 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Vol. Part F128815). Association for Computing Machinery. https://doi.org/10.1145/2487575.2487648

Connecting users across social media sites: A behavioral-modeling approach. / Zafarani, Reza; Liu, Huan.
KDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ed. / Rajesh Parekh; Jingrui He; Dhillon S. Inderjit; Paul Bradley; Yehuda Koren; Rayid Ghani; Ted E. Senator; Robert L. Grossman; Ramasamy Uthurusamy. Association for Computing Machinery, 2013. p. 41-49 2487648 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Vol. Part F128815).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zafarani, R & Liu, H 2013, Connecting users across social media sites: A behavioral-modeling approach. in R Parekh, J He, DS Inderjit, P Bradley, Y Koren, R Ghani, TE Senator, RL Grossman & R Uthurusamy (eds), KDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining., 2487648, Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, vol. Part F128815, Association for Computing Machinery, pp. 41-49, 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, Chicago, United States, 8/11/13. https://doi.org/10.1145/2487575.2487648

Zafarani R, Liu H. Connecting users across social media sites: A behavioral-modeling approach. In Parekh R, He J, Inderjit DS, Bradley P, Koren Y, Ghani R, Senator TE, Grossman RL, Uthurusamy R, editors, KDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery. 2013. p. 41-49. 2487648. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). doi: 10.1145/2487575.2487648

Zafarani, Reza ; Liu, Huan. / Connecting users across social media sites : A behavioral-modeling approach. KDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. editor / Rajesh Parekh ; Jingrui He ; Dhillon S. Inderjit ; Paul Bradley ; Yehuda Koren ; Rayid Ghani ; Ted E. Senator ; Robert L. Grossman ; Ramasamy Uthurusamy. Association for Computing Machinery, 2013. pp. 41-49 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

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Connecting users across social media sites: A behavioral-modeling approach

Abstract

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Keywords

ASJC Scopus subject areas

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