2013 ConnectingUsersAcrossSocialMedi

• (Zafarani & Liu, 2013) ⇒ Reza Zafarani, and Huan Liu. (2013). “Connecting Users Across Social Media Sites: A Behavioral-modeling Approach.” In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ISBN:978-1-4503-2174-7 doi:10.1145/2487575.2487648

Subject Headings:

Cited By

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Quotes

Author Keywords

• Cross-media analysis; data mining; mobius; user identification

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) for finding 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.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2013 ConnectingUsersAcrossSocialMedi	Huan Liu Reza Zafarani			Connecting Users Across Social Media Sites: A Behavioral-modeling Approach				10.1145/2487575.2487648		2013