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The COVID-19 pandemic has brought about trauma and uncertainty for vast swathes of the world population, including in Australia. One effect of this has been the growth of COVID-19 conspiracy theories, and general conspiracism. This article explores efforts by fascists and neo-Nazis to exploit the rise in conspiratorial thinking for recruitment and dissemination of their ideas. Five Australian conspiracist Telegram channels are studied for signs of fascist cross-pollination, and it is found that users with fascist sympathies attempt to influence the channels’ discourse through appeals to purported ideological and situational commonalities.

This paper observes some of the most distinguished characteristics of the Islamic State related to the use of modern technology and tries to drawn some important conclusions between the terrorist’s quasi state, modernity and technology. After the examination of the functioning of IS at the peak of its powers between 2014 and 2017, the analysis turns to terrorists’ various online activities. All of them are showing the Islamic State’s reliance on modern technology, especially IT, as one of the most important aspects of its terrorist activities that greatly contributed not only to the effectiveness, but to the essential definition of first modern terrorist quasi-state. The second part of the paper deals with the Islamic State`s fully reliance on technology in its own legitimization (both among Islamist rivals and “infidels”). The celebration and the fascination with modern technology as main IS characteristics make it different from other Islamist terrorist groups, and trying to establish relations between modernity and terrorism based on religious fundamentalism. The paper also tries to find answers to the question whether IS’s ultra-modern techno approach is responsible for its transformation from a classical fundamentalist terrorist group into some kind of modern political ideology and a social movement with totalitarian and murderous characteristics.

The process of becoming radicalized and joining extremist groups like Daesh, in countries with a Shi’a majority, such as Iran, is a controversial topic that has not received sufficient attention in the literature. This study examines Daesh’s media content in Farsi and seeks to provide an analysis of Daesh’s main messages, which have the primary objective of profoundly impacting their target audiences in Iran. This study collected data from 16 Iranian members of Daesh to discover how they were radicalized and why they decided to join Daesh. This study seeks to understand whether the media and Daesh’s propaganda are indeed the key reasons behind the radicalization of Daesh’s Iranian members and the creation of others’ perception of their mindsets against Iran and its Shi’a population, and to discover other possible factors that play a role in the radicalization process. While Daesh media and messages hold salience in relation to the Daeshization of some, studying such complex socio-political issues is rooted in an amalgamation of different personal, social, political, economic, and cultural push and pull factors. Such phenomena cannot, therefore, be reduced to only one of the mentioned elements.

Extremism has grown as a global problem for society in recent years, especially after the apparition of movements such as jihadism. This and other extremist groups have taken advantage of different approaches, such as the use of Social Media, to spread their ideology, promote their acts and recruit followers. The extremist discourse, therefore, is reflected on the language used by these groups. Natural language processing (NLP) provides a way of detecting this type of content, and several authors make use of it to describe and discriminate the discourse held by these groups, with the final objective of detecting and preventing its spread. Following this approach, this survey aims to review the contributions of NLP to the field of extremism research, providing the reader with a comprehensive picture of the state of the art of this research area. The content includes a first conceptualization of the term extremism, the elements that compose an extremist discourse and the differences with other terms. After that, a review description and comparison of the frequently used NLP techniques is presented, including how they were applied, the insights they provided, the most frequently used NLP software tools, descriptive and classification applications, and the availability of datasets and data sources for research. Finally, research questions are approached and answered with highlights from the review, while future trends, challenges and directions derived from these highlights are suggested towards stimulating further research in this exciting research area.

This report offers a preliminary analysis of the effectiveness of network disruptions in achieving one specific outcome: tackling terrorist violence. It analyses the relationship between network disruptions and deaths and injuries from terrorist attacks to determine whether there is support for the commonly made argument that network disruptions are an important counterterrorism tactic. Using a panel dataset of daily incidents of national-level network disruptions and terrorist attacks globally between 2016 and 2019, a fixed effects regression model shows that national-level network disruptions are not correlated with the number of people killed or injured in terrorist attacks. In addition, there is no correlation between a ban on social media platforms – specifically Facebook, Twitter and WhatsApp – and deaths or injuries from terrorist violence. This analysis has some limitations that make it difficult to make a causal claim, such as the non-random assignment of the treatment (that is, network disruptions) and the absence of a control variable to capture increased security around network disruptions. In general, these findings offer another perspective on the debate on network shutdowns, which often centres on the implications of shutdowns for human rights and democratic engagement and does not typically delve into empirical evidence on what network shutdowns can or cannot accomplish.

Social-media companies make extensive use of artificial intelligence in their efforts to remove and block terrorist content from their platforms. This paper begins by arguing that, since such efforts amount to an attempt to channel human conduct, they should be regarded as a form of regulation that is subject to rule-of-law principles. The paper then discusses three sets of rule-of-law issues. The first set concerns enforceability. Here, the paper highlights the displacement effects that have resulted from the automated removal and blocking of terrorist content and argues that regard must be had to the whole social-media ecology, as well as to jihadist groups other than the so-called Islamic State and other forms of violent extremism. Since rule by law is only a necessary, and not a sufficient, condition for compliance with rule-of-law values, the paper then goes on to examine two further sets of issues: the clarity with which social-media companies define terrorist content and the adequacy of the processes by which a user may appeal against an account suspension or the blocking or removal of content. The paper concludes by identifying a range of research questions that emerge from the discussion and that together form a promising and timely research agenda to which legal scholarship has much to contribute.