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A local expansion propagation algorithm for social link identification

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Abstract

Social link identification, that is to identify accounts across different online social networks that belong to the same user, is an important task in social network applications. Most existing methods to solve this problem directly applied machine learning classifiers on features extracted from user’s rich information. In practice, however, only some limited user information can be obtained because of privacy concerns. In addition, we observe that the existing methods cannot handle huge amount of potential account pairs from different online social networks. In this paper, we propose an effective method to address the above two challenges by expanding known anchor links (seed account pairs belonging to the same person). In particular, we leverage potentially useful information possessed by the existing anchor link and then develop a local expansion propagation model to identify new social links, which are taken as a generated anchor link to be used for iteratively identifying additional new social link. We evaluate our method on two most popular Chinese social networks. Experimental results show our proposed method can quickly find most of identity account pairs across different online social networks.

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Acknowledgements

We thank anonymous reviewers for their very useful comments and suggestions. This work was partially supported by grants from the National Natural Science Foundation of China (Grant No. U1533104, U1633110).

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Correspondence to Yuxiang Zhang.

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Zhang, Y., Fu, J., Yang, C. et al. A local expansion propagation algorithm for social link identification. Knowl Inf Syst 60, 545–568 (2019). https://doi.org/10.1007/s10115-018-1221-y

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