Multi-lingual detection of terrorist content on the Web

Mark Last, Alex Markov, Abraham Kandel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Scopus citations


Since the web is increasingly used by terrorist organizations for propaganda, disinformation, and other purposes, the ability to automatically detect terrorist-related content in multiple languages can be extremely useful. In this paper we describe a new, classification-based approach to multi-lingual detection of terrorist documents. The proposed approach builds upon the recently developed graph-based web document representation model combined with the popular C4.5 decision-tree classification algorithm. Evaluation is performed on a collection of 648 web documents in Arabic language. The results demonstrate that documents downloaded from several known terrorist sites can be reliably discriminated from the content of Arabic news reports using a simple decision tree.

Original languageEnglish
Title of host publicationIntelligence and Security Informatics - International Workshop, WISI 2006, Proceedings
Number of pages15
StatePublished - 14 Jul 2006
EventInternational Workshop on Intelligence and Security Informatics, WISI 2006 - Singapore, Singapore
Duration: 9 Apr 20069 Apr 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3917 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Workshop on Intelligence and Security Informatics, WISI 2006

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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