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Condizione: New.

Condizione: New.

Paperback. Condizione: Brand New. 100 pages. 8.66x5.91x0.23 inches. In Stock.

Taschenbuch. Condizione: Neu. Identifying Terrorist Affiliations through Social Network Analysis | Using Data Mining Techniques | Govand Ali | Taschenbuch | 100 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659932243 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In a world in which, since the fall of Twin Towers in New York on 9/11/2001, local ideologically inspired warfare becomes global all too quickly, terrorist groups like Al Quaeda and ISIS (Daesh) have successfully used modern computing technology and social networking environments to disperse their message, recruit new members, and plot attacks. This is especially true for such platforms as Twitter and encrypted mobile apps like Telegram or the clandestine Alrawi. As early detection of such activity is crucial to attack prevention data mining techniques have become increasingly important in the fight against the spread of global terrorist activity.This study employs data mining tools to mine Twitter for terrorist 'organizing' vocabulary and to pinpoint, through the analysis of (admittedly spares) tweet metadata, the most likely geographical location and connected identities behind the user accounts from which organizing or post-event information is disseminated. 100 pp. Englisch.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In a world in which, since the fall of Twin Towers in New York on 9/11/2001, local ideologically inspired warfare becomes global all too quickly, terrorist groups like Al Quaeda and ISIS (Daesh) have successfully used modern computing technology and social networking environments to disperse their message, recruit new members, and plot attacks. This is especially true for such platforms as Twitter and encrypted mobile apps like Telegram or the clandestine Alrawi. As early detection of such activity is crucial to attack prevention data mining techniques have become increasingly important in the fight against the spread of global terrorist activity.This study employs data mining tools to mine Twitter for terrorist 'organizing' vocabulary and to pinpoint, through the analysis of (admittedly spares) tweet metadata, the most likely geographical location and connected identities behind the user accounts from which organizing or post-event information is disseminated.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 100 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In a world in which, since the fall of Twin Towers in New York on 9/11/2001, local ideologically inspired warfare becomes global all too quickly, terrorist groups like Al Quaeda and ISIS (Daesh) have successfully used modern computing technology and social networking environments to disperse their message, recruit new members, and plot attacks. This is especially true for such platforms as Twitter and encrypted mobile apps like Telegram or the clandestine Alrawi. As early detection of such activity is crucial to attack prevention data mining techniques have become increasingly important in the fight against the spread of global terrorist activity.This study employs data mining tools to mine Twitter for terrorist 'organizing' vocabulary and to pinpoint, through the analysis of (admittedly spares) tweet metadata, the most likely geographical location and connected identities behind the user accounts from which organizing or post-event information is disseminated.