Signed network representation with novel node proximity evaluation

Pinghua Xu, Wenbin Hu*, Jia Wu, Weiwei Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Currently, signed network representation has been applied to many fields, e.g., recommendation platforms. A mainstream paradigm of network representation is to map nodes onto a low-dimensional space, such that the node proximity of interest can be preserved. Thus, a key aspect is the node proximity evaluation. Accordingly, three new node proximity metrics were proposed in this study, based on the rigorous theoretical investigation on a new distance metric - signed average first-passage time (SAFT). SAFT derives from a basic random-walk quantity for unsigned networks and can capture high-order network structure and edge signs. We conducted network representation using the proposed proximity metrics and empirically exhibited our advantage in solving two downstream tasks — sign prediction and link prediction. The code is publicly available.

Original languageEnglish
Pages (from-to)142-154
Number of pages13
JournalNeural Networks
Volume148
DOIs
Publication statusPublished - Apr 2022

Keywords

  • Signed social network
  • Network representation
  • Node proximity

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