IEEE Access (Jan 2022)

Link User Identities Across Social Networks Based on Contact Graph and User Social Behavior

  • Zhangfeng Yin,
  • Yang Yang,
  • Yuan Fang

DOI
https://doi.org/10.1109/ACCESS.2022.3165568
Journal volume & issue
Vol. 10
pp. 42432 – 42440

Abstract

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With the rapid development of Social Networking Services (SNSs), linking online user IDs is becoming increasingly important to internet service providers. Existing methods can achieve matching adjacent IDs between different services, where adjacent IDs mean the IDs that send message loggings at the same physical location. However, nonadjacent IDs also need to be matched in reality, which is a key challenge. In this paper, a new method based on users social behaviors and contact graph is put forward to realize linking of IDs across domains. This method can be used for matching both adjacent IDs and nonadjacent IDs. Specifically, all the IDs are mapped to contact graph. And we utilize a set matching algorithm based on the contact graph to find out the set of candidate IDs and generate confidence score by means of this algorithm to select the most appropriate matching. Our experimental results show that our algorithm is capable of identifying not only the set of adjacent IDs that belong to one same user but also the set of nonadjacent IDs that belong to one same user.

Keywords