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2012 | OriginalPaper | Buchkapitel

9. Authorship Analysis

verfasst von : Hsinchun Chen

Erschienen in: Dark Web

Verlag: Springer New York

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Abstract

Following the tragic events of September 11, 2001, researchers have been called upon to assume a larger role in the preservation of public safety and national security. One of the major challenges facing the intelligence and security community is monitoring of online communication mediums that are commonly used by terrorist groups. In this chapter, we addressed the online anonymity problem by successfully applying authorship analysis to English and Arabic extremist group web forum messages. The performance impact of different feature categories and techniques was evaluated across both languages. In order to facilitate enhanced writing style identification, a comprehensive list of online authorship features was incorporated. Additionally, an Arabic language model was created by adopting specific features and techniques to deal with the challenging linguistic characteristics of Arabic, including an elongation filter and a root clustering algorithm. A series of experiments were conducted to evaluate the efficacy of our models with results indicating a high level of success. Finally, a comparison of the English and Arabic language models and messages was made to aid the research community’s understanding of the dynamics of these group’s authorship tendencies.

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Literatur
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Zurück zum Zitat Al-Fedaghi, S. S. and Al-Anzi, F. (1989) A new algorithm to generate Arabic root-pattern forms. Proceedings of the 11th National Computer Conference (KFUPM, 1989), Dhahran, Saudi Arabia. Al-Fedaghi, S. S. and Al-Anzi, F. (1989) A new algorithm to generate Arabic root-pattern forms. Proceedings of the 11th National Computer Conference (KFUPM, 1989), Dhahran, Saudi Arabia.
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Zurück zum Zitat Larkey, L. S. and Connell, M. E. (2001). Arabic information retrieval at UMass in TREC-10 (TREC 2001), Gaithersburg, Maryland, (NIST 2001.) Larkey, L. S. and Connell, M. E. (2001). Arabic information retrieval at UMass in TREC-10 (TREC 2001), Gaithersburg, Maryland, (NIST 2001.)
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Zurück zum Zitat Peng, F., Schuurmans, D., Keselj, V., and Wang, S. (2003). Automated authorship attribution with character level language models. Paper presented at the 10th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2003). Peng, F., Schuurmans, D., Keselj, V., and Wang, S. (2003). Automated authorship attribution with character level language models. Paper presented at the 10th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2003).
Zurück zum Zitat Stamatatos, E., Fakotakis, N., and Kokkinakis, G. (2001). Computer-based Authorship Attribution without Lexical Measures. Computers and the Humanities, 35(2), 193–214.CrossRef Stamatatos, E., Fakotakis, N., and Kokkinakis, G. (2001). Computer-based Authorship Attribution without Lexical Measures. Computers and the Humanities, 35(2), 193–214.CrossRef
Zurück zum Zitat Zheng, R., Qin, Y., Huang, Z., and Chen, H. (2003). Authorship Analysis in Cybercrime Investigation. In Proceedings of the first NSF/NIJ Symposium, ISI 2003, Tucson, AZ, USA. Zheng, R., Qin, Y., Huang, Z., and Chen, H. (2003). Authorship Analysis in Cybercrime Investigation. In Proceedings of the first NSF/NIJ Symposium, ISI 2003, Tucson, AZ, USA.
Metadaten
Titel
Authorship Analysis
verfasst von
Hsinchun Chen
Copyright-Jahr
2012
Verlag
Springer New York
DOI
https://doi.org/10.1007/978-1-4614-1557-2_9

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