Abstract
Nowadays, online social networks (OSNs) play an important role in our daily lives. And it is very common for a person to have many profiles in different OSNs. However, different profiles in different OSNs of the same person are isolated from each other. User Identity Resolution (UIR) is the problem to recognize the same person in different OSNs. Most methods are mainly concerned with the profile attributes and they just use the information of profiles. In this paper, we propose a new algorithm, called Identity Matching based on Propagation of anchor links (IMP) which fully combines the profile attributes, the linkage information and the social actions, and solves the problem by expanding the anchor links (seed account pairs that belongs to the same user). In the IMP algorithm, we use the information of the nodes surrounding the anchor nodes and identify new links. As the spread of the anchor nodes, we can iteratively find more and more links. We conduct extensive experiments on Twitter and Facebook to evaluate our algorithm and the results show that our algorithm significantly improves the matching results and outperforms the baseline algorithms.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Vosecky, J., Hong, D., Shen, V.Y.: User identification across multiple social networks. In: First International Conference on Networked Digital Technologies, NDT 2009, pp. 360–365. IEEE (2009)
Zafarani, R., Liu, H.: 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, pp. 41–49. ACM (2013)
Malhotra, A., Totti, L., Meira Jr., W., Kumaraguru, P., Almeida, V.: Studying user footprints in different online social networks. In: Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012, pp. 1065–1070. IEEE Computer Society (2012)
Bartunov, S., Korshunov, A., Park, S.T., Ryu, W., Lee, H.: Joint link-attribute user identity resolution in online social networks. In: Proceedinghs of the Sixth SNA-KDD Workshop (2012)
Cortis, K., Scerri, S., Rivera, I., Handschuh, S.: An ontology-based technique for online profile resolution. Soc. Inf. 8238, 284–298 (2013)
Jain, P., Kumaraguru, P.: Finding Nemo: searching and resolving identities of users across online social networks (2012). arXiv:1212.6147v1
Kong, X., Zhang, J., Yu, P.S.: Inferring anchor links across multiple heterogeneous social networks. In: Proceedings of the 22nd ACM International Conference on Information and Knowledge management, pp. 179–188. ACM (2013)
Peled, O., Fire, M., Rokach, L., Elovici, Y.: Matching entities across online social networks. Neurocomputing 210, 91–106 (2016)
Zhu, X., Nie, Y., Jin, S., Li, A., Jia, Y.: Spammer Detection on Online Social Networks Based on Logistic Regression, pp. 29–40. Springer, Cham (2015)
Cui, Y., Pei, J., Tang, G., Luk, W.S., Jiang, D., Hua, M.: Finding email correspondents in online social networks. World Wide Web 16(2), 195–218 (2013)
Raad, E., Chbeir, R., Dipanda, A.: User profile matching in social networks. In: 13th International Conference on Network-Based Information Systems (NBiS), pp. 297–304. IEEE (2010)
Acknowledgement
This work was supported by NSFC (No. 61632019) and 863 project of China (No. 2015AA015403).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Li, S., Liang, W., Zhang, X. (2018). Recognize the Same Users across Multiple Online Social Networks. In: Meesad, P., Sodsee, S., Unger, H. (eds) Recent Advances in Information and Communication Technology 2017. IC2IT 2017. Advances in Intelligent Systems and Computing, vol 566. Springer, Cham. https://doi.org/10.1007/978-3-319-60663-7_31
Download citation
DOI: https://doi.org/10.1007/978-3-319-60663-7_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-60662-0
Online ISBN: 978-3-319-60663-7
eBook Packages: EngineeringEngineering (R0)