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‘Jihadism’ (also known as the jihadi movement) is a popular term that signifies the Islamic terror movement which thrives on extremist ideologies and violence. In addition to the conventional practices, the online medium is currently being employed for disseminating these extremist ideologies across the globe. Radicalisation and recruitment of geographically dispersed individuals as ‘jihadists’ for supporting Islamic terror activities tend to be the primary intent for using the digital platforms as the medium of communication in this context. One such initiative by the Lashkar-e-Taiba of Jammu and Kashmir was the release of the ‘Wyeth: The Resistance in Flow’, an e-magazine which was launched on April 2018. The first issue which was posted with an open access option was primarily designed to influence the Indian youth population through the radical interpretations of Islam. Hence, it is crucial to analyse and understand the jihadi discourse of the Wyeth magazine in order to curb and counter-attack such initiatives at its initial phase. For this purpose, the present study aims to examine the content of the Wyeth magazine and analyse the basic traits of the jihadi propaganda and its potential to aid in the self-radicalisation process.

Proliferation of social media platforms in recent past has resulted into upsurge in the number of users. Advent of these sites have paved way for the users to easily express share and communicate. In such a scenario, it is imperative to analyze the content and identify nasty content so as to avoid unpleasant situations. Machine learning techniques are extensively used for this purpose. In this paper, we propose a language model for the identification of hate speech in twitter data. Distil-BERT, a context aware embedding model along with Support Vector Machine (SVM) for the classification of hate speech has been used. SVM with a 10-fold cross validation and linear kernel has been found to provide better accuracy as compared to existing models. Results show that accuracy is improved with the use of context aware embedding model.

The Internet has made it possible for people to access just about any information they could possibly want. Conversely, it has given organizations a vehicle through which they can get their message out to a large audience. Hate groups have found the Internet particularly appealing, because they are able to get their uncensored message out to an unlimited number of people (ADL 2005). This is an issue that is not likely to go away.

This paper uses a computer-based frequency analysis to present an ideological discourse analysis of extremist ideologies in Daesh discourse. More specifically, by using a computer-assisted text analysis, the paper attempts to investigate the hidden extremist ideologies beyond the discourse of the first issue of Rumiyah, one of the main digital publications of Daesh. The paper’s main objectives are to expose hidden ideologies beyond the mere linguistic form of discourse, to offer better linguistic understanding of the manipulative use of language in religious discourse, and to highlight the relevance of using a computer-based frequency analysis to discourse studies and corpus linguistics. The paper also employs van Dijk’s ideological discourse analysis, by adopting his positive self-presentation and negative other-presentation strategies. Findings reveal that Daesh discourse in Rumiyah is rhetorically structured to hide the manipulative ideologies of its users, which in turn functions to reformulate the social, political and religious attitudes of its readers.

This paper compares the social media posts of ISIS foreign fighters to those of ISIS supporters. We examine a random sample of social media posts made by violent foreign fighters (n = 14; 2000 posts) and non-violent supporters (n = 18; 2000 posts) of the Islamic State of Iraq and Syria (ISIS) (overall n = 4,000 posts), from 2009 to 2015. We used a mixed-method study design. Our qualitative content analyses of the 4,000 posts identified five themes: Threats to in-group, societal grievances, pursuit for significance, religion, and commitment issues. Our quantitative comparisons found that the dominant themes in the foreign fighters’ online content were threats to in-group, societal grievances, and pursuit for significance, while religion and commitment issues were dominant themes in the supporters’ online content. We also identified thematic variations reflecting individual attitudes that emerged during the 2011–2015 period, when major geopolitical developments occurred in Syria and Iraq. Finally, our quantitative sentiment-based analysis found that the supporters (10 out of 18; 56%) posted more radical content than the foreign fighters (5 out of 14; 36%) on social media.

By exploring lessons learned from Ethiopia and Finland, this article challenges two assumptions about online hate speech research. First, it challenges the assumption that the best way to understand controversial concepts such as online hate speech is to determine how closely they represent or mirror some underlying set of facts or state of affairs online or in social media. Second, it challenges the assumption that academic research should be seen as separate from the many controversies that surround online hate speech debates globally. In its place, the article proposes the theory of “commentary” as a comparative research framework aimed at explaining how the messy and complex world of online and social media practices is articulated as hate speech over other ways of imagining this growing problem in global digital media environments.