Learning to Correlate Accounts Across Online Social Networks: An Embedding-Based Approach

Published Online:https://doi.org/10.1287/ijoc.2019.0911

References

  • Bengio Y, Schwenk H, Sencal JS, Morin F, Gauvain JL (2003) A neural probabilistic language model. J. Machine Learn. Res. 3:1137–1155.Google Scholar
  • Elmagarmid AK, Ipeirotis PG, Verykios VS (2007) Duplicate record detection: A survey. IEEE Trans. Knowledge Data Engrg. 19(1):1–16.CrossrefGoogle Scholar
  • Goga O, Perito D, Lei H, Teixeira R, Sommer R (2013) Large-scale correlation of accounts across social networks. Technical Report No. ICSI TR-13-002, International Computer Science Institute, Berkley, CA.Google Scholar
  • Grover A, Leskovec J (2016) Node2Vec: Scalable feature learning for networks. Proc. ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 855–864.Google Scholar
  • Gutmann MU, Hyvärinen A (2012) Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics. J. Machine Learn. Res. 13(1):307–361.Google Scholar
  • Hashemifar S, Xu J (2014) Hubalign: An accurate and efficient method for global alignment of protein–protein interaction networks. Bioinformatics 30(17):438–444.CrossrefGoogle Scholar
  • Huang Z, Lin DKJ (2009) The time-series link prediction problem with applications in communication surveillance. INFORMS J. Comput. 21(2):286–303.LinkGoogle Scholar
  • Klau GW (2009) A new graph-based method for pairwise global network alignment. BMC Bioinformatics 10(1):S59.CrossrefGoogle Scholar
  • Koutra D, Tong H, Lubensky D (2013) Big-align: Fast bipartite graph alignment. Proc. IEEE Internat. Conf. Data Mining (IEEE, Piscataway, NJ), 389–398.Google Scholar
  • LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 521(7553):436–444.CrossrefGoogle Scholar
  • Lee C, Pham M, Jeong MK, Kim D, Lin DKJ, Chavalitwongse WA (2015) A network structural approach to the link prediction problem. INFORMS J. Comput. 27(2):249–267.LinkGoogle Scholar
  • Li XB, Sarkar S (2011) Protecting privacy against record linkage disclosure: A bounded swapping approach for numeric data. Inform. Systems Res. 22(4):774–789.LinkGoogle Scholar
  • Li Z, Fang X, Bai X, Sheng ORL (2015) Utility-based link recommendation for online social networks. Management Sci. 63(6):1657–2048.Google Scholar
  • Liu L, Cheung WK, Li X, Liao L (2016) Aligning users across social networks using network embedding. Proc. Internat. Joint Conf. Artificial Intelligence (AAAI Press, New York), 1774–1780.Google Scholar
  • Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J (2013) Distributed representations of words and phrases and their compositionality. Proc. Internat. Conf. Neural Inform. Processing Systems (Curran Associates, Red Hook, NY), 3111–3119.Google Scholar
  • Mu X, Zhu F, Lim EP, Xiao J, Wang J, Zhou ZH (2016) User identity linkage by latent user space modelling. Proc. ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 1775–1784.Google Scholar
  • Perozzi B, Al-Rfou R, Skiena S (2014) DeepWalk: Online learning of social representations. Proc. ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 701–710.Google Scholar
  • Singh R, Xu J, Berger B (2008) Global alignment of multiple protein interaction networks with application to functional orthology detection. Proc. Natl. Acad. Sci. USA 105(35):12763–12768.Google Scholar
  • Strickland DM, Barnes E, Sokol JS (2005) Optimal protein structure alignment using maximum cliques. Oper. Res. 53(3):389–402.LinkGoogle Scholar
  • Tan S, Guan Z, Cai D, Qin X, Bu J, Chen C (2014) Mapping users across networks by manifold alignment on hypergraph. Proc. AAAI Conf. Artificial Intelligence, Quebec City, Canada, 159–165.Google Scholar
  • Tang J, Qu M, Wang M, Zhang M, Yan J, Mei Q (2015) Line: Large-scale information network embedding. Proc. Internat. Conf. World Wide Web, Florence, Italy, 1067–1077.Google Scholar
  • Yang J, Zhang XD (2016) Predicting missing links in complex networks based on common neighbors and distance. Sci. Rep. 6:Article 38208.Google Scholar
  • Yang YC (2010) Web user behavioral profiling for user identification. Decision Support Systems 49(3):261–271.CrossrefGoogle Scholar
  • Yang YC, Liu H, Cai Y (2013) Discovery of online shopping patterns across websites. INFORMS J. Comput. 25(1):161–176.LinkGoogle Scholar
  • Yang YC, Padmanabhan B, Liu H, Wang X (2012) Discovery of periodic patterns in sequence data: A variance-based approach. INFORMS J. Comput. 24(3):372–386.LinkGoogle Scholar
  • Zafarani R, Liu H (2013) Connecting users across social media sites: A behavioral-modeling approach. Proc. ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 41–49.Google Scholar
  • Zhang Y, Tang J, Yang Z, Pei J, Yu PS (2015) Cosnet: Connecting heterogeneous social networks with local and global consistency. Proc. ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 1485–1494.Google Scholar
  • Zhang Z, Zeng DD, Abbasi A, Peng J, Zheng X (2013) A random walk model for item recommendation in social tagging systems. ACM Trans. Management Inform. Systems 4(2):1–24.Google Scholar
  • Zhou X, Liang X, Du X, Zhao J (2017) Structure based user identification across social networks. IEEE Trans. Knowledge Data Engrg. 30(6):1178–1191.Google Scholar
  • Zhou X, Liang X, Zhang H, Ma Y (2016) Cross-platform identification of anonymous identical users in multiple social media networks. IEEE Trans. Knowledge Data Engrg. 28(2):411–424.CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.