A social network analysis approach to detecting suspicious online financial activities

Lei Tang, Geoffrey Barbier, Huan Liu, Jianping Zhang

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

11 Scopus citations

Abstract

Social network analysis techniques can be applied to help detect financial crimes. We discuss the relationship between detecting financial crimes and the social web, and use select case studies to illustrate the potential for applying social network analysis techniques. With the increasing use of online financing services and online financial activities, it becomes more challenging to find suspicious activities among massive numbers of normal and legal activities.

Original languageEnglish (US)
Title of host publicationAdvances in Social Computing - Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, Proceedings
Pages390-397
Number of pages8
DOIs
StatePublished - Dec 24 2010
Event3rd International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010 - Bethesda, MD, United States
Duration: Mar 30 2010Mar 31 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6007 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010
CountryUnited States
CityBethesda, MD
Period3/30/103/31/10

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Keywords

  • Crime detection
  • Social network analysis
  • Social networks

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Tang, L., Barbier, G., Liu, H., & Zhang, J. (2010). A social network analysis approach to detecting suspicious online financial activities. In Advances in Social Computing - Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, Proceedings (pp. 390-397). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6007 LNCS). https://doi.org/10.1007/978-3-642-12079-4_49