​Tweeting terrorism: Vernacular conceptions of Muslims and terror in the wake of the Manchester Bombing on Twitter

Both vernacular security studies and critical terrorism studies (CTS) offer constructivist analyses of security couched in understandings of security speak. However, neither adequately take account of the ways in which social media presents important opportunities for greater insight into how terrorism is constructed. This study analyses tweets posted after the 2017 Manchester bombing, exploring how jihadist terror attacks are constructed on social media. To do this, we combine social network analysis, as a sampling method, with discourse analysis. The study finds that Twitter provides a platform for diverse terrorism discourses to be expressed and contested. This indicates a literate lay audience within post-attack narratives, self-aware of dominant social constructions of “Muslim terrorism”. Indeed, it suggests an audience that, on Twitter, is hardly only audience but seeks to speak security itself. Insights are gleaned with respect to depicting, defending, and critiquing Muslims, constructing what it means to be a terrorist, portrayals of victimhood, and how terror events feed into broader critiques of “political correctness” and “liberal” politics. Therefore, the analysis also provides further insights into the portrayal and (self-)positioning of Muslims in the wake of a jihadist attack and nuances accounts of Muslims’ securitisation qua terror

Tweeting terrorism: Vernacular conceptions of Muslims and terror in the wake of the Manchester Bombing on Twitter

Both vernacular security studies and critical terrorism studies (CTS) offer constructivist analyses of security couched in understandings of security speak. However, neither adequately take account of the ways in which social media presents important opportunities for greater insight into how terrorism is constructed. This study analyses tweets posted after the 2017 Manchester bombing, exploring how jihadist terror attacks are constructed on social media. To do this, we combine social network analysis, as a sampling method, with discourse analysis. The study finds that Twitter provides a platform for diverse terrorism discourses to be expressed and contested. This indicates a literate lay audience within post-attack narratives, self-aware of dominant social constructions of “Muslim terrorism”. Indeed, it suggests an audience that, on Twitter, is hardly only audience but seeks to speak security itself. Insights are gleaned with respect to depicting, defending, and critiquing Muslims, constructing what it means to be a terrorist, portrayals of victimhood, and how terror events feed into broader critiques of “political correctness” and “liberal” politics. Therefore, the analysis also provides further insights into the portrayal and (self-)positioning of Muslims in the wake of a jihadist attack and nuances accounts of Muslims’ securitisation qua terror

Evaluating digital policy interventions: studies in violence prevention, deradicalization, and investor protection

Social media platforms allow individuals without great technical knowledge or financial capital to spread violent content and radical messages among a large audience, bypassing traditional media. As violence and radical actions cause significant economic damage and undermine democratic institutions, security agencies have responded by using the same platforms to target at-risk individuals with their prevention programs. The literature has shown that such online programs can be effective in reducing victimization and perpetration rates. However, despite the large number of programs implemented, there is a significant lack of rigorous impact evaluations. This thesis contributes to the literature by developing a conceptual framework for evaluating the impact and economic efficiency of online programs for crime prevention in general. Furthermore, it contributes by evaluating the impact of two online programs in the areas of violence prevention and deradicalization. To reassess the impact of such online programs in a different prevention context, the thesis also evaluates a measure for investor protection in the context of the Bitcoin cryptocurrency

Temporal models for mining, ranking and recommendation in the Web

Due to their first-hand, diverse and evolution-aware reflection of nearly all areas of life, heterogeneous temporal datasets i.e., the Web, collaborative knowledge bases and social networks have been emerged as gold-mines for content analytics of many sorts. In those collections, time plays an essential role in many crucial information retrieval and data mining tasks, such as from user intent understanding, document ranking to advanced recommendations. There are two semantically closed and important constituents when modeling along the time dimension, i.e., entity and event. Time is crucially served as the context for changes driven by happenings and phenomena (events) that related to people, organizations or places (so-called entities) in our social lives. Thus, determining what users expect, or in other words, resolving the uncertainty confounded by temporal changes is a compelling task to support consistent user satisfaction. In this thesis, we address the aforementioned issues and propose temporal models that capture the temporal dynamics of such entities and events to serve for the end tasks. Specifically, we make the following contributions in this thesis: (1) Query recommendation and document ranking in the Web - we address the issues for suggesting entity-centric queries and ranking effectiveness surrounding the happening time period of an associated event. In particular, we propose a multi-criteria optimization framework that facilitates the combination of multiple temporal models to smooth out the abrupt changes when transitioning between event phases for the former and a probabilistic approach for search result diversification of temporally ambiguous queries for the latter. (2) Entity relatedness in Wikipedia - we study the long-term dynamics of Wikipedia as a global memory place for high-impact events, specifically the reviving memories of past events. Additionally, we propose a neural network-based approach to measure the temporal relatedness of entities and events. The model engages different latent representations of an entity (i.e., from time, link-based graph and content) and use the collective attention from user navigation as the supervision. (3) Graph-based ranking and temporal anchor-text mining inWeb Archives - we tackle the problem of discovering important documents along the time-span ofWeb Archives, leveraging the link graph. Specifically, we combine the problems of relevance, temporal authority, diversity and time in a unified framework. The model accounts for the incomplete link structure and natural time lagging in Web Archives in mining the temporal authority. (4) Methods for enhancing predictive models at early-stage in social media and clinical domain - we investigate several methods to control model instability and enrich contexts of predictive models at the “cold-start” period. We demonstrate their effectiveness for the rumor detection and blood glucose prediction cases respectively. Overall, the findings presented in this thesis demonstrate the importance of tracking these temporal dynamics surround salient events and entities for IR applications. We show that determining such changes in time-based patterns and trends in prevalent temporal collections can better satisfy user expectations, and boost ranking and recommendation effectiveness over time

Global Terrorism Index 2022: Measuring the Impact of Terrorism

This is the ninth edition of the Global Terrorism Index (GTI). The report provides a comprehensive summary of the key global trends and patterns in terrorism over the last decade. The calculation of the GTI score takes into account not only deaths, but also incidents, hostages, and injuries from terrorism, weighted over a five-year period. The GTI report is produced by the Institute for Economics & Peace (IEP) using data from TerrorismTracker and other sources. TerrorismTracker provides event records on terrorist attacks since 1 January 2007. The dataset contains over 60,500 terrorist incidents for the period 2007 to 2021

Mapping (Dis-)Information Flow about the MH17 Plane Crash

Digital media enables not only fast sharing of information, but also disinformation. One prominent case of an event leading to circulation of disinformation on social media is the MH17 plane crash. Studies analysing the spread of information about this event on Twitter have focused on small, manually annotated datasets, or used proxys for data annotation. In this work, we examine to what extent text classifiers can be used to label data for subsequent content analysis, in particular we focus on predicting pro-Russian and pro-Ukrainian Twitter content related to the MH17 plane crash. Even though we find that a neural classifier improves over a hashtag based baseline, labeling pro-Russian and pro-Ukrainian content with high precision remains a challenging problem. We provide an error analysis underlining the difficulty of the task and identify factors that might help improve classification in future work. Finally, we show how the classifier can facilitate the annotation task for human annotators

Creating Chaos Online

Unmasks the disinformation propagated by Russian trolling in public discours

Political conflict as moral conflict : multiculturalism and the nation in Germany (2015-2017)

Cette thèse examine, depuis une perspective durkheimienne, le conflit politique en Allemagne sur le multiculturalisme, l’immigration, et l’identité nationale. L’analyse se fait dans la période entre le début de la crise des réfugiés en 2015 et l’élection fédérale allemande de septembre 2017. J’identifie quatre idéaux moraux, soit des visions idéales de la communauté allemande qui motivent les acteurs politique : l’idéal des Autonomen qui rejettent tout forme de pouvoir et de domination, l’idéal du Verfassungspatriotismus (le patriotisme constitutionnel) de la SPD (et une partie de la CDU), l’idéal de la nation (ethno)culturelle de la plupart de l’AfD (et la CSU et la WerteUnion), et l’idéal de la nation biologique de l’extrême droite. Au cœur de chaque idéal est un objet sacré qui sert d’autorité morale qui légitimant des prescriptions morales et qui amène à une série de vérités morales et de jugements moraux, la totalité duquel Émile Durkheim identifie comme un fait moral. Pour les Autonomen et les adhérents du Verfassungspatriotismus, l’objet sacré est l’individu conçu à travers le concept de la dignité humaine. Pour les autres, l’objet sacré est la nation allemande, conçue en termes (ethno)culturels ou en termes biologiques. Cette thèse argumente que ces idéaux moraux sont intrinsèquement profanatoires, dans le sens que les prescriptions morales d’un objet sacré (la dignité humaine) violent directement l’objet sacré de l’autre (la nation), et vice-versa. Ces idéaux sont tous en concurrence pour le pouvoir et l’influence, avec comme but d’avoir accès au pouvoir étatique allemand. Le résultat est un conflit politique qui traduit essentiellement un conflit moral. Ces conflits ont lieu dans le domaine légal, au sein des partis politique, et à travers la violence politique. Ces conflits touchent un nombre de sujets clés comme la liberté d’expression, le multiculturalisme, et l’extrémisme politique. La présente thèse cherche à comprendre ces conflits à travers le prisme du concept durkheimien du fait moral, et développe une sociologie du conflit moral durkheimien. Cette thèse s’inspire également de la théorie de conflit de Randall Collins, qui s’inspire elle aussi de l’œuvre de Durkheim.This dissertation examines, from a Durkheimian perspective, political conflict in Germany around the issues of multiculturalism, immigration, and national identity within the context of the Refugee Crisis beginning in 2015 and ending roughly with the German Federal Election in September 2017. It identifies four moral ideals, or ideal visions of the German community, that motivated political actors during this period: the Autonomen ideal that rejects all forms of power and domination; the ideal of Verfassungspatriotismus (Constitutional Patriotism) of the SPD (and parts of the CDU); the ideal of the cultural or ethnocultural nation of much of the AfD (and the CSU and WerteUnion); and the ideal of the biological nation on the far-right. At the heart of each moral ideal is a sacred object that serves as a moral authority that legitimates certain moral prescriptions, and leads to a set of moral truths and moral judgments, the totality of which Émile Durkheim identifies as a moral fact. For the Autonomen and adherents of Verfassungspatriotismus the sacred object is the individual understood through the concept of human dignity. For others the sacred object is the German nation, understood either in an (ethno)cultural sense or a biological sense. As the dissertation argues, these different moral ideals are inherently profanatory to each other, such that the moral prescriptions inspired by one sacred object (human dignity) directly violate the sacred object of the other (the nation), and vice-versa. These ideals all compete with each other for power and influence within the German political sphere as a means to gain access to (or to dismantle) state power. The result is political conflict that takes place essentially within a moral framework. These conflicts occur in the legal domain, in battles over party leadership and membership, and through political violence; they touch on a number of key issues such as free speech, multiculturalism, and political extremism. This dissertation seeks to understand these conflicts through the prism of Durkheim’s concept of the moral fact and to develop a Durkheimian sociology of moral conflict. In this analysis, the dissertation draws on Randall Collins’ conflict theory, which Durkheim’s work also largely inspires