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Extracting Social Structure from Dark Web Metadata

Authors:
Elizabeth Phillips
Jason R. C. Nurse
Michael Goldsmith
Sadie Creese

Keywords: Social Network Analysis; Dark Web Forum; Jihadist forums; Social Structure

Abstract:
This paper explores various Social Network Analysis (SNA) techniques in order to identify a range of potentially ‘important’ members of Islamic Networks within Dark Web Forums. For this experiment, we conducted our investigation on five forums collected in previous work as part of the DarkWeb Forum portal and built upon the tool support created in our previous research in order to visualise and analyse the network. Whilst existing work attempts to identify these structures through state-of- the-art Computational Linguistic techniques, our work relies on the communication metadata alone. Our analysis involved first calculating a range of SNA metrics to better understand the group members, and then apply unsupervised learning in order to create clusters that would help classify the Dark Web Forums users into hierarchical clusters. In order to create our social networks, we investigated the effect of repeated author resolution and various weighting schemes on the ranking of forum members by creating four social networks per forum and evaluating the correlation of the top n users (for n = 10; 20; 30; 40; 50 and 100). Our results identified that varying the weighting schemes created more consistent ranking schemes than varying the repeated author resolution.

Pages: 97 to 102

Copyright: Copyright (c) IARIA, 2015

Publication date: November 15, 2015

Published in: conference

ISSN: 2326-9294

ISBN: 978-1-61208-443-5

Location: Barcelona, Spain

Dates: from November 15, 2015 to November 20, 2015