Fraud analysis and detection for real-time messaging communications on social networks

Liang Chun Chen, Chien Lung Hsu, Nai Wei Lo, Kuo Hui Yeh*, Ping Hsien Lin

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

7 Scopus citations


With the successful development and rapid advancement of social networking technology, people tend to exchange and share information via online social networks, such as Facebook and LINE.Massive amounts of information are aggregated promptly and circulated quickly among people. However, with the enormous volume of human-interactions, various types of swindles via online social networks have been launched in recent years. Effectively detecting fraudulent activities on social networks has taken on increased importance, and is a topic of ongoing interest. In this paper, we develop a fraud analysis and detection system based on realtime messaging communications, which constitute one of the most common human-interacted services of online social networks. An integrated platform consisting of various text-mining techniques, such as natural language processing, matrix processing and content analysis via a latent semantic model, is proposed. In the system implementation, we first collect a series of fraud events, all of which happened in Taiwan, to construct analysis modules for detecting such fraud events. An Android-based application is then built for alert notification when dubious logs and fraud events happen.

Original languageEnglish
Pages (from-to)2267-2274
Number of pages8
JournalIEICE Transactions on Information and Systems
Issue number10
StatePublished - 10 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
Copyright © 2017 The Institute of Electronics, Information and Communication Engineers.


  • Facebook
  • Fraud analysis
  • Latent semantic analysis
  • Natural language processing
  • Social networks


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