Bridge enhanced signed directed network embedding

Yiqi Chen, Tieyun Qian, Huan Liu, Ke Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Signed directed networks with positive or negative links convey rich information such as like or dislike, trust or distrust. Existing work of sign prediction mainly focuses on triangles (triadic nodes) motivated by balance theory to predict positive and negative links. However, real-world signed directed networks can contain a good number of bridge edges which, by definition, are not included in any triangles. Such edges are ignored in previous work, but may play an important role in signed directed network analysis. In this paper, we investigate the problem of learning representations for signed directed networks. We present a novel deep learning approach to incorporating two social-psychologic theories, balance and status theories, to model both triangles and bridge edges in a complementary manner. The proposed framework learns effective embeddings for nodes and edges which can be applied to diverse tasks such as sign prediction and node ranking. Experimental results on three real-world datasets of signed directed social networks verify the essential role of "bridge" edges in signed directed network analysis by achieving the state-of-the-art performance.

Original languageEnglish (US)
Title of host publicationCIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management
EditorsNorman Paton, Selcuk Candan, Haixun Wang, James Allan, Rakesh Agrawal, Alexandros Labrinidis, Alfredo Cuzzocrea, Mohammed Zaki, Divesh Srivastava, Andrei Broder, Assaf Schuster
PublisherAssociation for Computing Machinery
Pages773-782
Number of pages10
ISBN (Electronic)9781450360142
DOIs
StatePublished - Oct 17 2018
Event27th ACM International Conference on Information and Knowledge Management, CIKM 2018 - Torino, Italy
Duration: Oct 22 2018Oct 26 2018

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other27th ACM International Conference on Information and Knowledge Management, CIKM 2018
CountryItaly
CityTorino
Period10/22/1810/26/18

Keywords

  • Balance theory
  • Signed directed network embedding
  • Status theory

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

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  • Cite this

    Chen, Y., Qian, T., Liu, H., & Sun, K. (2018). Bridge enhanced signed directed network embedding. In N. Paton, S. Candan, H. Wang, J. Allan, R. Agrawal, A. Labrinidis, A. Cuzzocrea, M. Zaki, D. Srivastava, A. Broder, & A. Schuster (Eds.), CIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management (pp. 773-782). (International Conference on Information and Knowledge Management, Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3269206.3271738