RT Article
T1 Interpreting text and image relations in violent extremist discourse: a mixed methods approach for big data analytics
JF Terrorism and political violence
VO 31
IS 3
SP 454
OP 474
A1 Bateman, John A.
A1 O'Halloran, Kay L. 1958-
A1 Tan, Sabine
A1 Wignell, Peter
A1 Pham, Duc-Son
A1 Grossman, Michele 1957-
A1 Vande Moere, Andrew
A2 O'Halloran, Kay L. 1958-
A2 Tan, Sabine
A2 Wignell, Peter
A2 Pham, Duc-Son
A2 Grossman, Michele 1957-
A2 Vande Moere, Andrew
LA English
YR 2019
UL https://krimdok.uni-tuebingen.de/Record/1698562160
AB This article presents a mixed methods approach for analysing text and image relations in violent extremist discourse. The approach involves integrating multimodal discourse analysis with data mining and information visualisation, resulting in theoretically informed empirical techniques for automated analysis of text and image relations in large datasets. The approach is illustrated by a study which aims to analyse how violent extremist groups use language and images to legitimise their views, incite violence, and influence recruits in online propaganda materials, and how the images from these materials are re-used in different media platforms in ways that support and resist violent extremism. The approach developed in this article contributes to what promises to be one of the key areas of research in the coming decades: namely the interdisciplinary study of big (digital) datasets of human discourse, and the implications of this for terrorism analysis and research.
K1 Big data analytics
K1 Dabiq
K1 Data Mining
K1 information visualisation
K1 Islamic State (ISIS and ISIL)
K1 Mixed Methods
K1 multimodal discourse analysis
K1 terrorism analysis
K1 violent extremist discourse
DO 10.1080/09546553.2016.1233871