Online Library

Universities play a vital role in carrying out research on issues where security-sensitive material is relevant. This guidance document concerns the storage and circulation of security- sensitive research material. If circulated carelessly, such material is sometimes open to misinterpretation by the authorities, and can put authors in danger of arrest and prosecution under, for example, counter-terrorism legislation. Certain procedures for independently registering and storing this material – through research ethics processes – are recommended in this guidance.

This study examined the literature on online terrorism studies between 2001 and 2022 and compared themes across journal segments and funded research. The results showed that there is a relationship between funding and the number of publications in recent years. While themes in the core terrorism journals more likely to follow the traditional terrorism studies, funded research (e.g. Computer Science Journals) focus more on social media, far-right groups and hate speech utilizing new research tools such as machine learning and text mining techniques. These new tools enable researchers to study different dimensions of the phenomenon, but these works are not published in terrorism journals. The results also point to a gap between core terrorism journals and Computer Science journals, which heralds at least two potential developments in the future: i) emergence of specialized journals focusing on terrorism and concepts like social media, populism, hate speech, text mining, machine learning and so on; and ii) more collaborative outputs between terrorism researchers and computer scientists.

The paper investigates the potential effects user features have on hate speech classification. A quantitative analysis of Twitter data was conducted to better understand user characteristics, but no correlations were found between hateful text and the characteristics of the users who had posted it. However, experiments with a hate speech classifier based on datasets from three different languages showed that combining certain user features with textual features gave slight improvements of classification performance. While the incorporation of user features resulted in varying impact on performance for the different datasets used, user network-related features provided the most consistent improvements.

The backbone of the “skull mask” transnational neo-fascist accelerationist network—whose nodes include terror groups such as Atomwaffen, the Base, and Feuerkrieg Division—is a group of organizations that grew out of Iron March, a neo-fascist web forum that was active from 2011 to 2017. The history of the Iron March network shows that violent extremist movements can develop from online communities even in the absence of a territorial base and without regular in-person contact between members. Iron March provided a closed social space where young neo-fascists who did not fit in well in established neo-fascist organizations could create a transnational collective identity. Eventually, Iron March users sought each other out in person and created local groups that remained networked together by virtue of their common origin in the community created on the web forum. The network’s transition from activism to terrorism was facilitated by the introduction of violent ritualistic initiation practices derived from the writings of the Order of Nine Angles, which helped to habituate members to violence as well as to create a sense of shared membership in a militant elite.

This thesis asks why and how terrorist organizations use the Internet to achieve three strategic goals: 1) the dissemination of propaganda, 2) recruitment and 3) fundraising. It is immediately apparent that the Internet offers a number of advantages, including low cost, global reach, and anonymity. Nonetheless, terrorist organizations vary in their exploitation of these advantages according to their immediate objectives. To explain these variations, this thesis presents a comparative study of Al Qaeda, the Islamic State of Iraq and Syria (ISIS), and the Taliban. This study considers how different objectives render distinct narratives and thereby affect how those narratives leverage images and information in the dissemination of propaganda. Similarly, targets of recruitment vary according to the objectives of the respective organizations; this primarily affects their use of social media, including Facebook, YouTube, Twitter, and other applications. Fundraising methods also vary, from local means (extortion, narcotics, smuggling) to contemporary exploitation of digital platforms like PayPal and cell phone applications enabling anonymous donations. This thesis concludes that the sophistication of terrorist organizations online requires an equally sophisticated response that is as essential to the fight against violent extremism as kinetic operations.

The present paper contributes to the research on the activities of far-right actors on social media by examining the interconnections between far-right actors and groups on Telegram platform using network analysis. The far-right network observed on Telegram is highly decentralized, similarly to the far-right networks found on other social media platforms. The network is divided mostly along the ideological and national lines, with the communities related to 4chan imageboard and Donald Trump’s supporters being the most influential. The analysis of the network evolution shows that the start of its explosive growth coincides in time with the mass bans of the far-right actors on mainstream social media platforms. The observed patterns of network evolution suggest that the simultaneous migration of these actors to Telegram has allowed them to swiftly recreate their connections and gain prominence in the network thus casting doubt on the effectiveness of deplatforming for curbing the influence of far-right and other extremist actors.