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This paper investigates whether the counter-terrorism measures developed and implemented within the European Union have a universal character and are equally effective in the context of various types of terrorism. The authors focus on the strategies applicable to the terrorist activities online, since information and communication technology is perceived as the fastest growing and continually changing field of the terrorist threat. So far, most of the counteractions and security strategies have been subordinated to the jihadism combating. However, in recent years, the significant growth of threats coming from far-right and far-left terrorist activities has been observed. It raises questions about the capability of instruments to prevent and combat other types of terrorism as well as jihadism. The research was conducted in particular, on the basis of international organizations’ reports, the authors’ observations, and practitioners’ remarks. As follows from its results, there are significant differences in the phenomenon, current trends, and modus operandi of the perpetrators in the jihadi, far-right, and far-left terrorism. Consequently, it is possible to conclude that the effectiveness of chosen countermeasures, subordinated – as a rule – to the fighting of the jihadi extremists, is doubtful in preventing and combating far-right and far-left terrorism.

Extremism has been a problematic term to define and suggests different and opposing meanings. This study explores how Twitter users conceptualize extremism in Arabic and express their opinions/arguments to construct the term. A corpus of tweets was collected from Twitter API using the word ‘تطرف أو متطرف’ in Arabic for extremist/extremism. A topic modeling algorithm was then applied to the dataset to uncover latent associated concepts underlying extremism, followed by a critical discourse analysis using Van Dijk’s Sociocognitive approach. The discursive and linguistic strategies used by Twitter users to support and justify their views of extremism were examined. The findings demonstrate an ideological influence that controls the concept of extremism, keeping it open to manipulation to serve shared interests and goals. Arab users of Twitter use extremism to promote their groups’ positive schema against others-negative schema.

This study analyzed the contents of three of the most popular Arabic‐language online message boards regarding the attacks of September 11, 2001 on the United States. Although terrorists claimed that the attacks were committed in the name of Islam, those who posted messages on all three forums rejected this claim. More than 43% of the messages condemned the attacks as a criminal act of terrorism that contradicts the core teachings of Islam. Some 30% saw some justification behind the attacks, even if they felt sorry for the victims and their families. However, those participants viewed the attacks as a political, rather than a religious, issue.

The dramatic growth of the Web has motivated researchers to extract knowledge from enormous repositories and to exploit the knowledge in myriad applications. In this study, we focus on natural language processing (NLP) and, more concretely, the emerging field of affective computing to explore the automation of understanding human emotions from texts. This paper continues previous efforts to utilize and adapt affective techniques into different areas to gain new insights. This paper proposes two novel feature extraction methods that use the previous sentic computing resources AffectiveSpace and SenticNet. These methods are efficient approaches for extracting affect-aware representations from text. In addition, this paper presents a machine learning framework using an ensemble of different features to improve the overall classification performance. Following the description of this approach, we also study the effects of known feature extraction methods such as TF-IDF and SIMilarity-based sentiment projectiON (SIMON). We perform a thorough evaluation of the proposed features across five different datasets that cover radicalization and hate speech detection tasks. To compare the different approaches fairly, we conducted a statistical test that ranks the studied methods. The obtained results indicate that combining affect-aware features with the studied textual representations effectively improves performance. We also propose a criterion considering both classification performance and computational complexity to select among the different methods.

This briefing is the first in ISD’s Gaming and Extremism Series exploring the role online gaming plays in the strategy of far-right extremists in the UK and around the world. This is part of a broader programme on the “Future of Extremism” being delivered by ISD in the second half of 2021, charting the transformational shifts in the extremist threat landscape two decades since 9/11, and the policy strategies required to counter the next generation of extremist threats. The series will include reports exploring extremist activity on four gaming-related platforms: Steam, Discord, DLive and Twitch.

This study explores the internal dynamics and networks of terrorist groups in cyberspace—in particular, Al-Qaeda and the Islamic State of Iraq and al-Sham (ISIS). Using a “Global Cyberterrorism Dataset” that features data on cyberterror attacks between 2011 and 2016, this research analyzes these two terrorist groups through the lens of a cyber-conflict theory that integrates conflict theory with Jaishankar’s space transition theory. Through a network analysis methodology, we examine the invisible relationships and connections between the national origins and target countries of cyberterror attacks. The analysis focuses on the networks of national origins of terrorists and victims, network structures of Al-Qaeda and ISIS actors, and clustering networks of Al-Qaeda and ISIS cyberterrorists. Results indicate that terror in cyberspace is ubiquitous, more flexible than traditional terrorism, and that cyberattacks mostly occurred within the countries of origin. We conclude by discussing the complex features of cyberterror networks and identify some of the geostrategic implications of the divergent cyber strategies adopted by Al-Qaeda and ISIS.