Journal Article |
A Quantitative Approach To Understanding Online Antisemitism
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A new wave of growing antisemitism, driven by fringe Web communities, is an increasingly worrying presence in the socio-political realm. The ubiquitous and global nature of the Web has provided tools used by these groups to spread their ideology to the rest of the Internet. Although the study of antisemitism and hate is not new, the scale and rate of change of online data has impacted the efficacy of traditional approaches to measure and understand this worrying trend. In this paper, we present a large-scale, quantitative study of online antisemitism. We collect hundreds of million comments and images from alt-right Web communities like 4chan’s Politically Incorrect board (/pol/) and the Twitter clone, Gab. Using scientifically grounded methods, we quantify the escalation and spread of antisemitic memes and rhetoric across the Web. We find the frequency of antisemitic content greatly increases (in some cases more than doubling) after major political events such as the 2016 US Presidential Election and the “Unite the Right” rally in Charlottesville. Furthermore, this antisemitism appears in tandem with sharp increases in white ethnic nationalist content on the same communities. We extract semantic embeddings from our corpus of posts and demonstrate how automated techniques can discover and categorize the use of antisemitic terminology. We additionally examine the prevalence and spread of the antisemitic “Happy Merchant” meme, and in particular how these fringe communities influence its propagation to more mainstream services like Twitter and Reddit. Taken together, our results provide a data-driven, quantitative framework for understanding online antisemitism. Our open and scientifically grounded methods serve as a framework to augment current qualitative efforts by anti-hate groups, providing new insights into the growth and spread of antisemitism online.
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2018 |
Finkelstein, J., Zannettou, S., Bradlyn, B. and Blackburn, J. |
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Journal Article |
Paris And Nice Terrorist Attacks: Exploring Twitter And Web Archives
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The attacks suffered by France in January and November 2015, and then in the course of 2016, especially the Nice attack, provoked intense online activity both during the events and in the months that followed. The digital traces left by this reactivity and reactions to events gave rise, from the very first days and even hours after the attacks, to a ‘real-time’ institutional archiving by the National Library of France (Bibliothèque nationale de France) and the National Audio-visual Institute (Institut national de l’audiovisuel). The results amount to millions of archived tweets and URLs. This article seeks to highlight some of the most significant issues raised by these relatively unprecedented corpora, from collection to exploitation, from online stream of data to its mediation and re-composition. Indeed, web archiving practices in times of emergency and crises are significant, almost emblematic, loci to explore the human and technical agencies, and the complex temporalities, of ‘born-digital’ heritage. The cases examined here emphasize the way these ‘emergency collections’ challenge the perimeters and the very nature of web archives as part of our digital and societal heritage, and the guiding visions of its governance and mission. Finally, the present analysis underlines the need for a careful contextualization of the design process – both of original web pages or tweets and of their archived images – and of the tools deployed to collect, retrieve and analyse them.
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2019 |
Schafer, V., Truc, G. and Badouard, R. |
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Journal Article |
Detection Of Jihadism In Social Networks Using Big Data
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Social networks are being used by terrorist organizations to distribute messages with the intention of influencing people and recruiting new members. The research presented in this paper focuses on the analysis of Twitter messages to detect the leaders orchestrating terrorist networks and their followers. A big data architecture is proposed to analyze messages in real time in order to classify users according to diferent parameters like level of activity, the ability to infuence other users, and the contents of their messages. Graphs have been used to analyze how the messages propagate through the network, and this involves a study of the followers based on retweets and general impact on other users. Ten, fuzzy clustering techniques were used to classify users in profiles, with the advantage over other classifcations techniques of providing a probability for each profile instead of a binary categorization. Algorithms were tested using public database from Kaggle and other Twitter extraction techniques. The resulting profiles detected automatically by the system were manually analyzed, and the parameters that describe each profile correspond to the type of information that any expert may expect. Future applications are not limited to detecting terrorist activism. Human resources departments can apply the power of profle identification to automatically classify candidates, security teams can detect undesirable clients in the financial or insurance sectors, and immigration officers can extract additional insights with these
techniques.
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2019 |
Rebollo, C. S., Puente, C., Palacios, R., Piriz, C., Fuentes, J. P. and Jarauta, J. |
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Journal Article |
ISIS at Its Apogee: The Arabic Discourse on Twitter and What We Can Learn From That About ISIS Support and Foreign Fighters
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We analyze 26.2 million comments published in Arabic language on Twitter, from July 2014 to January 2015, when Islamic State of Iraq and Syria (ISIS)’s strength reached its peak and the group was prominently expanding the territorial area under its control. By doing that, we are able to measure the share of support and aversion toward the Islamic State within the online Arab communities. We then investigate two specific topics. First, by exploiting the time granularity of the tweets, we link the opinions with daily events to understand the main determinants of the changing trend in support toward ISIS. Second, by taking advantage of the geographical locations of tweets, we explore the relationship between online opinions across countries and the number of foreign fighters joining ISIS.
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2019 |
Ceron, A., Curini, L. and Iacus, S. M. |
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Journal Article |
The Power Of A Good Story: Narrative Persuasion in Extremist Propaganda and Videos Against Violent Extremism
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The perceived threat of extremist online propaganda has generated a need for countermeasures applicable to large audiences. The dissemination of videos designed to counter violent extremism (CVE videos) is widely discussed. These videos are often described as “counter-narratives,” implying that narrativity is a crucial factor for their effectiveness. Experimental research testing this assumption is rare and direct comparisons of narrativity effects between propaganda and CVE videos are lacking. To fill this gap, we conducted two experiments (one in a laboratory and one online) in which we confronted German participants with different religious affiliations and from various cultural backgrounds (NStudy 1 = 338 and NStudy 2 = 155) with Islamist extremist or right-wing extremist propaganda videos and with corresponding CVE videos. The results confirmed that narrativity (a) increases persuasive processing of propaganda and CVE videos, (b) fosters amplification intentions regarding these videos, and (c) increases attraction to extremists versus counter-activists. Thus, our studies highlight the crucial role of narrativity in both extremist propaganda and video-based CVE approaches.
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2018 |
Frischlich, L., Rieger, D., Morten, A. and Bente, G. |
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Book |
Media Persuasian in the Islamic State
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Since the declaration of the War on Terror in 2001, militant groups such as al-Qaeda and the Islamic State have used the internet to disseminate their message and persuade people to commit violence. While many books have studied their operational strategies and battlefield tactics, Media Persuasion in the Islamic State is the first to analyze the culture and psychology of militant persuasion.
Drawing upon decades of research in cultural psychiatry, cultural psychology, and psychiatric anthropology, Neil Krishan Aggarwal investigates how the Islamic State has convinced people to engage in violence since its founding in 2003. Through analysis of hundreds of articles, speeches, videos, songs, and bureaucratic documents in English and Arabic, the book traces how the jihadist Abu Musab al-Zarqawi created a new culture and psychology, one that would pit Sunni Muslims against all others after the U.S.-led invasion of Iraq. Aggarwal tracks how Osama bin Laden and al-Zarqawi disagreed over the goal of militancy in jihad before reaching a détente in 2004 and how al-Qaeda in Iraq merged with five other groups to diffuse its militant cultural identity in 2006 before taking advantage of the Syrian civil war to emerge as the Islamic State. Aggarwal offers a definitive analysis of how culture is created, debated, and disseminated within militant organizations like the Islamic State. Psychiatrists, psychologists, and area-studies experts will find a comprehensive, systematic method for analyzing culture and psychology so they can partner with political scientists, policy makers, and counterterrorism experts in crafting counter-messaging strategies against militants.
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2019 |
Krishan Aggarwal, N. |
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