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Please use this identifier to cite or link to this item: http://dspace.univ-ouargla.dz/jspui/handle/123456789/20981

Titre: Datawarehouse-based approach for the analysis of terrorism-related activities in social networks
Auteur(s): DJABALLAH, Kamel AHSENE
BOUKHALFA, Kamel
BOUSSAID, Omar
Mots-clés: Social Neworks
Data Warehouses
Terrorism
Sentiment Analysis
OLAP
Twitter
Issue Date: 5-Mar-2019
Editeur: Université Kasdi Merbah Ouargla
Collection/Numéro: 2019;
Résumé: Social network analysis techniques for activities related to terrorism are mainly based on data mining techniques. These techniques do not take into account the various axes of analysis allowing a study according to several facets. In this article we propose a comparison study of these techniques. We present our approach of analyzing these activities, based on Data warehouse and OLAP analysis. We aim to improve the analysis of these cyber threats. OLAP analysis allows us to explore social networks to detect dangerous content in the direction of targeted cyber threats. Our approach is based on five-tier architecture: (1) data sources; (2) ETL; (3) Data warehouse; (4) Analysis; (5) Presentation. In our experimentations, we used Twitter to detect and analyze the incitement to terrorism and determine the users supported the terrorism. We proposed a datamart with a metric named score, calculated using a data mining technique. Also, we used OLAP analysis techniques, based on the history of positive scores, to determine the users inciting terrorism, their locations and their retweets.
Description: Le 2eme Conference Internationale sur intelligence Artificielle et les Technologies Information ICAIIT 2019
URI: http://dspace.univ-ouargla.dz/jspui/handle/123456789/20981
Appears in Collections:2. Faculté des nouvelles technologies de l’information et de la communication

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