Reading jihad: Mapping the shifting themes of <i>Inspire</i> magazine

Droogan, Julian; Peattie, Shane

doi:10.1080/09546553.2016.1211527

Cited by 31 publications

(26 citation statements)

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“…While the total amount of texts might seem small in number, the 9 texts in the French corpus represent a 90% sample of the total Dar al Islam publication, as only 10 issues were published (Buril, 2017). Similarly, the 11 issues of Dabiq and the 9 issues of Inspire used in the English corpus represent 73% and 64% of the total Dabiq and Inspire publications, as only 15 and 14 issues were published, respectively (Droogan & Peattie, 2016, Wignell et al, 2017c. The complete volumes of these publications were not included in the corpora because they were either not available from the source (see below) or they were corrupted files that were not computer-readable.…”

Section: Methodsmentioning

confidence: 99%

“…Researchers have drawn on Inspire and Dabiq as data in order to examine narrative themes (Droogan & Peattie, 2016), the ISIS world view (Wignell et al, 2017b), radicalisation strategies (Ingram, 2017), and to compare and contrast ISIS, the Taliban, and al-Qaeda (Aggarwal, 2017;Ingram, 2017;Novenario, 2016). Other researchers have been interested in mapping out the evolution of the language used by ISIS more generally (Vergani & Bliuc, 2015).…”

Section: The Violent Extremism and Publications Of The Islamic State mentioning

confidence: 99%

“…Other researchers have been interested in mapping out the evolution of the language used by ISIS more generally (Vergani & Bliuc, 2015). The methods have been equally wide-ranging, drawing on content analysis (Novenario, 2016), radical narrative analysis (Ingram, 2016), thematic network analysis (Droogan & Peattie, 2016), and multimodal social semiotics (Wignell et al, 2017a(Wignell et al, , 2017b. Although some computerised analysis has been applied to these texts (e.g.…”

Section: The Violent Extremism and Publications Of The Islamic State mentioning

confidence: 99%

“…The perpetrators of attacks have either identified themselves as members of groups like al-Qaeda or ISIS, and/or such groups have claimed responsibility for the attacks. Many of the perpetrators of attacks have been identified as British and French nationals, often in possession of illegal terrorist materials; some of these individuals were radicalised as a result of communication with the groups or via the groups' media propaganda (Droogan & Peattie, 2016;Novenario, 2016). The availability of extremist materials in languages like English and French ensures that the groups have possible influence that extends far beyond the Arabic-speaking heartlands where the groups' headquarters are based geographically.…”

Section: Introductionmentioning

confidence: 99%

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A corpus-driven comparison of English and French Islamist extremist texts

Baker

Vessey

2022

IJCL

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Using corpus linguistics and qualitative, manual discourse analysis, this paper compares English and French extremist texts to determine how messages in different languages draw upon similar and distinct discursive themes and linguistic strategies. Findings show that both corpora focus on religion and rewards (i.e. for faith) and strongly rely on othering strategies. However, the English texts are concerned with world events whereas the French texts focus on issues specific to France. Also, while the English texts use Arabic code-switching as a form of legitimation, the French texts use a formal register and quotation from scripture in discussions of permissions, rights, obligations and laws. Finally, the English texts refer to and justify violence to a greater extent than the French texts. This paper contributes to the field of terrorism studies and the field of corpus linguistics by presenting a new approach to corpus-driven studies of discourse across more than one language.

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Section: Methodsmentioning

confidence: 99%

Section: The Violent Extremism and Publications Of The Islamic State mentioning

confidence: 99%

Section: The Violent Extremism and Publications Of The Islamic State mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A corpus-driven comparison of English and French Islamist extremist texts

Baker

Vessey

2022

IJCL

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“…However, a fundamental challenge is reducing the barriers to machine understanding (Alonso, ), given even in binary classification schemes some measure of disagreement exists (Hashemi & Hall, , ). Approaches to classification tend to either be fully machine (e.g., Alghamdi & Selamat, ; Sabbah, Selamat, & Selamat, ; Scrivens, Davies, Frank, & Mei, ) or human (e.g., Droogan & Peattie, ; Ligon, Hall, & Braun, ; Torres, Jordán, & Horsburgh, ; Torres‐Soriano, ). Very few studies to date compare performance of humans and machines when classifying the underlying themes of radicalizing content.…”

Section: Introductionmentioning

confidence: 99%

Do Machines Replicate Humans? Toward a Unified Understanding of Radicalizing Content on the Open Social Web

Hall¹,

Logan²,

Ligon³

et al. 2019

Policy & Internet

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The advent of the Internet inadvertently augmented the functioning and success of violent extremist organizations. Terrorist organizations like the Islamic State in Iraq and Syria (ISIS) use the Internet to project their message to a global audience. The majority of research and practice on web‐based terrorist propaganda uses human coders to classify content, raising serious concerns such as burnout, mental stress, and reliability of the coded data. More recently, technology platforms and researchers have started to examine the online content using automated classification procedures. However, there are questions about the robustness of automated procedures, given insufficient research comparing and contextualizing the difference between human and machine coding. This article compares output of three text analytics packages with that of human coders on a sample of one hundred nonindexed web pages associated with ISIS. We find that prevalent topics (e.g., holy war) are accurately detected by the three packages whereas nuanced concepts (Lone Wolf attacks) are generally missed. Our findings suggest that naïve approaches of standard applications do not approximate human understanding, and therefore consumption, of radicalizing content. Before radicalizing content can be automatically detected, we need a closer approximation to human understanding.

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Case Study: Constructing an Imagined Community in Al‐Qaeda's Magazine Inspire

Tarantini¹

2020

The Handbook of Magazine Studies

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Reading jihad: Mapping the shifting themes of Inspire magazine

Cited by 31 publications

References 0 publications

A corpus-driven comparison of English and French Islamist extremist texts

A corpus-driven comparison of English and French Islamist extremist texts

Do Machines Replicate Humans? Toward a Unified Understanding of Radicalizing Content on the Open Social Web

Case Study: Constructing an Imagined Community in Al‐Qaeda's Magazine Inspire

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