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Terrorism is a global challenge of the 21 st century. The Kenya Westgate Mall attack and Garrissa University attacks in 2015 and the Libya suicide bombings, did not only claim the lives of many, but also had great political consequences. The advancements, ease of access and availability of information and communication technologies (ICT) is blamed for the increases in terrorist attacks: for instance, the Internet and especially, social media. This is because through the Internet, terrorist organizations such as ISIS have come up with innovative ways to recruit new members, to train and even disseminate ideologies. However, the terrorist opponents (counter-terrorism organizations) also have developed innovative counter-measures using ICT. Therefore, understanding and structuring terrorism in this digital age has enhanced the complexity in addition to multiple stakeholders involved in terrorism related incidences, intertwined causal-relationships, and the uncertainties in the mode of operandi of the terrorists. In this study, theory of synergetics is applied both as a theoretical and methodological approach to try structure the terrorism problem. Secondary data sources such as journal articles on terrorism related incidences and search terms (i.e. terrorism AND technology, terrorism AND Internet), were used by the researchers’ to identify and include relevant documents in the study. Following the inclusion and exclusion criteria, the researchers remained with only 405 documents from which using the qualitative software Nvivo, a word cloud was developed to pictorially visualize the terrorism problem. Thereafter, relying on synergetics and using results from the word cloud, the researchers’ were able to create a conceptual model. The findings from the analysis of the conceptual model showed that technology plays a critical role in the fight against terrorism as it appears to be part of each of the various components of synergetics, namely, order parameters, system elements, internal and external constraints, control parameters and environment.

Although social media have become important venues for right-wing populist (RWP) campaigns, the content, selection, and effects of RWP messages on social media remain largely unknown. Using content and panel analysis in two studies, we investigated the potential reciprocal relationship between RWP communication on social media and citizens’ anti-immigrant attitudes, anti-elitist attitudes, and feelings of anger and anxiety. In Study 1, we analyzed 13,358 Facebook posts from German and Austrian political parties and their leading candidates. Among our results, RWP actors conveyed anti-immigrant and anti-elitist messages more often than non-RWP actors, and anti-immigrant messages especially induced negative emotional responses among followers of RWP actors. In Study 2, our analysis of data from a two-wave panel study with 559 respondents revealed that anti-immigrant attitudes drove selective exposure to RWP content on Facebook, which consequently fueled anti-immigrant attitudes, and that selective exposure to such content increased individuals’ anti-elitist attitudes and anxiety.

This study explores the beliefs, narratives and ideologies that lead to violent radicalism underpinned by an abusive interpretation of Islam, with a view to understanding of the causes and remedies for violent radicalisation. The research was conducted through analysis and empirical data collection through 145 stakeholder and primary fieldwork interviews in four Member States; Denmark, France, Germany and the UK. The interview sample was intended to capture the diversity of the Muslim ‘field’ in each country as far as possible

In this article, we propose a general model of data collection from social media, in the context of terrorism research, focusing on recent studies of jihadists. By analyzing Twitter data collection methods in the existing research, we show that the methods used are prone to sampling biases, and that the sampled datasets are not sufficiently filtered or validated to ensure reliability of conclusions derived from them. Alternatively, we propose some best practices for the collection of data in future research on jihadist using social media (as well as other kinds of terrorist groups). Given the similarity of the methodological challenges posed by research on almost all social media platforms, in the context of terrorism studies, the critique and recommendations offered remain relevant despite the recent shift of most jihadists from Twitter to Telegram and other forms of social media.

Over the past decade, a large number of extremist and hate groups have turned to internet platforms to inspire mass violence. Currently, there is little reliable evidence on how such campaigns radicalize targeted audiences. We provide systematic, large-scale, microevidence on the effect of Islamic State propaganda on social media. We use several machine learning algorithms to detect recruitment messages in online propaganda, identify their dissemination on Twitter, and quantify the reactions of exposed users. Analyzing content produced by the Islamic State between 2015 and 2016 shows that propaganda conveying the material, spiritual, and social benefits of joining ISIS increased online support for the group, while content displaying brutal violence decreased endorsement of ISIS across a wide range of videos. Only the group’s most extreme supporters reacted positively to violent propaganda.