Multi-lingual detection of terrorist content on the Web

Mark Last; Alex Markov; Abraham Kandel

doi:10.1007/11734628_3

Multi-lingual detection of terrorist content on the Web

Mark Last, Alex Markov, Abraham Kandel

Department of Software and Information Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

17 Scopus citations

Abstract

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 language	English
Title of host publication	Intelligence and Security Informatics - International Workshop, WISI 2006, Proceedings
Pages	16-30
Number of pages	15
DOIs	https://doi.org/10.1007/11734628_3
State	Published - 14 Jul 2006
Event	International Workshop on Intelligence and Security Informatics, WISI 2006 - Singapore, Singapore Duration: 9 Apr 2006 → 9 Apr 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3917 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Workshop on Intelligence and Security Informatics, WISI 2006
Country/Territory	Singapore
City	Singapore
Period	9/04/06 → 9/04/06

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/11734628_3

Cite this

Last, M., Markov, A., & Kandel, A. (2006). Multi-lingual detection of terrorist content on the Web. In Intelligence and Security Informatics - International Workshop, WISI 2006, Proceedings (pp. 16-30). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3917 LNCS). https://doi.org/10.1007/11734628_3

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title = "Multi-lingual detection of terrorist content on the Web",

abstract = "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.",

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year = "2006",

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Last, M, Markov, A & Kandel, A 2006, Multi-lingual detection of terrorist content on the Web. in Intelligence and Security Informatics - International Workshop, WISI 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3917 LNCS, pp. 16-30, International Workshop on Intelligence and Security Informatics, WISI 2006, Singapore, Singapore, 9/04/06. https://doi.org/10.1007/11734628_3

Multi-lingual detection of terrorist content on the Web. / Last, Mark; Markov, Alex; Kandel, Abraham.
Intelligence and Security Informatics - International Workshop, WISI 2006, Proceedings. 2006. p. 16-30 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3917 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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.

AB - 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.

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Multi-lingual detection of terrorist content on the Web

Abstract

Publication series

Conference

ASJC Scopus subject areas

UN SDGs

Access to Document

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