Journal Article |
Countering Violent Extremism Online: The Experiences of Informal Counter Messaging Actors
View Abstract
The online space is a haven for extremists of all kinds. Although efforts to remove violent and extremist content are increasing, there is a widely accepted need to also contest extremist messages with counter messages designed to undermine and disrupt extremist narratives. While the majority of academic focus has been on large and well‐funded efforts linked to governments, this article considers the experiences of informal actors who are active in contesting extremist messaging but who lack the support of large institutions. Informal actors come without some of the baggage that accompanies formal counter-message campaigns, which have been attacked as lacking in credibility and constituting “just more government propaganda.” This has been noted by some of the wider countering violent extremism industry and the appetite for incorporating “real‐world” content in their campaigns seems to be rising. This article fills a gap in our knowledge of the experiences of informal counter-messaging actors. Through a series of in‐depth qualitative interviews it demonstrates that, despite the potentially serious risks of incorporating greater levels of informal content, there is an appetite among informal actors to engage with formal campaigns where they can be selective over who they work with and maintain a degree of control.
|
2019 |
Lee, B. |
View
Publisher
|
Report |
‘The Baghdadi Net’: How A Network of ISIL-Supporting Accounts Spread Across Twitter
View Abstract
Islamic State of Iraq and Syria (ISIL) supporters fanned out large amounts of Arabic content across Twitter all through the week in the wake of the news surrounding the death of Abu Bakr al Baghdadi. Many accounts were exhibiting strong and multiple signals of automated behavior1, spawning every hour, on the hour, and Institute for Strategic Dialogue (ISD) researchers monitored and tracked these accounts, and their tactics for the past week following the news. Twitter, and accounts specifically designed to report ISIL activity, were limiting some of the effects of what researchers were calling the ‘Baghdadi Net.’ However, it was clear the accounts were able to generate again, sometimes seconds within a takedown period, and spread video, and audio, as well as new ISIL-news content. Many accounts used western avatars, linked to real people, as well as hashtags that were trending across the Middle East and North Africa, including those being used in the Iraq and Lebanon protests. Latching on to trending topics is a well-documented tactic by ISIL and other groups to increase impressions and overall reach of content. As of Friday, the accounts were tweeting out audio content produced by al Furqan media heralding the ascension of the new ISIL leader Abu Ibrahim al Hashimi al Qurashi.
|
2019 |
Ayad, M. |
View
Publisher
|
Journal Article |
Elites and foreign actors among the alt-right: The Gab social media platform
View Abstract
Content regulation and censorship of social media platforms is increasingly discussed by governments and the platforms themselves. To date, there has been little data-driven analysis of the effects of regulated content deemed inappropriate on online user behavior. We therefore compared Twitter — a popular social media platform that occasionally removes content in violation of its Terms of Service — to Gab — a platform that markets itself as completely unregulated. Launched in mid 2016, Gab is, in practice, dominated by individuals who associate with the “alt right” political movement in the United States. Despite its billing as “The Free Speech Social Network,” Gab users display more extreme social hierarchy and elitism when compared to Twitter. Although the framing of the site welcomes all people, Gab users’ content is more homogeneous, preferentially sharing material from sites traditionally associated with the extremes of American political discourse, especially the far right. Furthermore, many of these sites are associated with state-sponsored propaganda from foreign governments. Finally, we discovered a significant presence of German language posts on Gab, with several topics focusing on German domestic politics, yet sharing significant amounts of content from U.S. and Russian sources. These results indicate possible emergent linkages between domestic politics in European and American far right political movements. Implications for regulation of social media platforms are discussed.
|
2019 |
Zhou, Y., Dredze, M., Broniatowski, D. A. and Adler, W. D. |
View
Publisher
|
Journal Article |
Predicting Behavioural Patterns in Discussion Forums using Deep Learning on Hypergraphs
View Abstract
Online discussion forums provide open workspace allowing users to share information, exchange ideas, address problems, and form groups. These forums feature multimodal posts and analyzing them requires a framework that can integrate heterogeneous information extracted from the posts, i.e. text, visual content and the information about user interactions with the online platform and each other. In this paper, we develop a generic framework that can be trained to identify communication behavior and patterns in relation to an entity of interest, be it user, image or text in internet forums. As the case study we use the analysis of violent online political extremism content, which has been a major challenge for domain experts. We demonstrate the generalizability and flexibility of our framework in predicting relational information between multimodal entities by conducting extensive experimentation around four practical use cases.
|
2019 |
Arya, D., Rudinac, S. and Worring, M. |
View
Publisher
|
Journal Article |
A comparison of ISIS foreign fighters and supporters social media posts: an exploratory mixed-method content analysis
View Abstract
This paper compares the social media posts of ISIS foreign fighters to those of ISIS supporters. We examine a random sample of social media posts made by violent foreign fighters (n = 14; 2000 posts) and non-violent supporters (n = 18; 2000 posts) of the Islamic State of Iraq and Syria (ISIS) (overall n = 4,000 posts), from 2009 to 2015. We used a mixed-method study design. Our qualitative content analyses of the 4,000 posts identified five themes: Threats to in-group, societal grievances, pursuit for significance, religion, and commitment issues. Our quantitative comparisons found that the dominant themes in the foreign fighters’ online content were threats to in-group, societal grievances, and pursuit for significance, while religion and commitment issues were dominant themes in the supporters’ online content. We also identified thematic variations reflecting individual attitudes that emerged during the 2011–2015 period, when major geopolitical developments occurred in Syria and Iraq. Finally, our quantitative sentiment-based analysis found that the supporters (10 out of 18; 56%) posted more radical content than the foreign fighters (5 out of 14; 36%) on social media.
|
2019 |
Dillon, L., Neo, L. S. and Freilich, J. D. |
View
Publisher
|
Journal Article |
Modeling Islamist Extremist Communications on Social Media using Contextual Dimensions: Religion, Ideology, and Hate
View Abstract
Terror attacks have been linked in part to online extremist content. Although tens of thousands of Islamist extremism supporters consume such content, they are a small fraction relative to peaceful Muslims. The efforts to contain the ever-evolving extremism on social media platforms have remained inadequate and mostly ineffective. Divergent extremist and mainstream contexts challenge machine interpretation, with a particular threat to the precision of classification algorithms. Our context-aware computational approach to the analysis of extremist content on Twitter breaks down this persuasion process into building blocks that acknowledge inherent ambiguity and sparsity that likely challenge both manual and automated classification. We model this process using a combination of three contextual dimensions — religion, ideology, and hate — each elucidating a degree of radicalization and highlighting independent features to render them computationally accessible. We utilize domain-specific knowledge resources for each of these contextual dimensions such as Qur’an for religion, the books of extremist ideologues and preachers for political ideology and a social media hate speech corpus for hate. Our study makes three contributions to reliable analysis: (i) Development of a computational approach rooted in the contextual dimensions of religion, ideology, and hate that reflects strategies employed by online Islamist extremist groups, (ii) An in-depth analysis of relevant tweet datasets with respect to these dimensions to exclude likely mislabeled users, and (iii) A framework for understanding online radicalization as a process to assist counter-programming. Given the potentially significant social impact, we evaluate the performance of our algorithms to minimize mislabeling, where our approach outperforms a competitive baseline by 10.2% in precision.
|
2019 |
Kursuncu, U., Gaur, M., Castillo, C., Alambo, A. Thirunarayan, K., Shalin, V., Achilov, D., Budak Arpinar, I. and Sheth, A. |
View
Publisher
|