Report |
Far‑Right Extremism and Digital Book Publishing
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Digital publishing, sale and distribution of books have contributed significantly to the dissemination and mainstreaming of far‐right extremist (FRE) material in the 21st century. Historical and contemporary books that espouse politically and ideologically motivated violence circulate widely and easily online, in both FRE and mainstream spaces. Such books include, but are not limited to: the speeches of Adolf Hitler, William L. Pierce’s The Turner Diaries, Theodore Kaczynski’s Industrial Society and its Future (The Unabomber Manifesto), James Mason’s Siege, and anthologies produced by the Iron March forum and Terrorgram Collective.
Technology companies have already taken steps to remove some of the most notorious FRE books from sale, distribution and discussion. In the case of extremist novels, such as The Turner Diaries, searches typically meet a dead end and return purchasing recommendations of books on anti‐racism and de‐radicalisation rather than hate fiction.
This report recommends that the companies surveyed extend this practice to other FRE materials documented below, using available techniques to understand and interrupt the formation of a network of recommendations which leads individuals towards publications advocating political violence. The report also recommends the use of available techniques (such as machine learning) to scrutinise the nature of self‐published materials, with the aim of preventing reproductions of materials that are refused classification from being published spuriously under misleading titles or pseudonyms.
The report is agnostic on whether such companies should stock the speeches of Adolf Hitler, for instance, focusing instead on potential problems in the way the affordances of search technologies provide ready‐made FRE libraries.
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2024 |
Young, H. and Boucher, G.M. |
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Journal Article |
Shifting Patterns of Extremist Discourse on Facebook: Analyzing Trends and Developments During the Israel-Hamas Conflict
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This working paper explores trends in extremist Facebook data from July 2023 to June 2024. We examined engagement, sentiment, and topics within Facebook groups categorized as anti-Israel/Semitic, anti-Palestine/Muslim, and anti-both, mapping these trends against five major events related to the recent Israel-Hamas conflict. Our findings support the hypothesis that shifts in trends correspond with these key events, showing varying patterns across different group categories. We observed decreased activity proportion in anti-both groups and increased activity proportion in the two one-sided hate groups at the conflict’s onset. This pattern reversed after the Israeli troop withdrawal from Khan Yunis, Gaza. During the conflict, negative content proportion surged, and neutral content proportion fell in all the three group categories. Anti-Palestine/Muslim groups’ discourses shifted from religious to social media activism and political/protest around the time the war began, while anti-Israel/Semitic groups moved from political/protest to religious topics a couple of weeks before the war.
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2024 |
Nefriana, R., Yan, M., Diab, A., Yu, W., Wheeler, D.L., Miller, A., Hwa, R. and Lin, Y.R. |
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VOX-Pol Blog |
Nazis at the salad bar: The National Workers’ Alliance and mixed, unclear, and unstable ideology
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2024 |
Gill, G. |
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Journal Article |
Social network size and endorsement of political violence in the US
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In recent years, the United States (US) has witnessed a rise in political violence. Prior research has found that an individual’s social network is associated with their likelihood of engaging in various forms of violence, but research on social networks and political violence in the US context is limited. This study examined associations between social network size and endorsement of political violence in a recent nationally representative survey and explored how the relationship varied by use of social media as a major news source, perceptions of the government as an enemy, and membership in a marginalized or privileged racial or ethnic group.
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2024 |
Schleimer, J.P., Reeping, P.M., Robinson, S.L. and Wintemute, G.J. |
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Chapter |
Artificial Intelligence (AI) and Radicalization
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This chapter explores the manner in which extremist groups could use artificial intelligence (AI) in the future to promote their narratives and recruit people to their causes. It looks at four broad use cases, namely generative AI, chat bots, gaming, and predictive analytics, and analyzes how extremists could adapt their propaganda and outreach efforts to incorporate new and innovative AI-powered techniques which would revolutionize their efficacy. The chapter then analyzes the current regulatory environment with regard to online content to assess the extent to which we are prepared for the AI revolution as it pertains to political messaging and the dissemination of information online. The chapter also touches on what all of this means for our civil liberties and what they might look like in a digital era that is also experiencing decentralization and a decline in Big Tech’s monopoly. It concludes with some thoughts on what we can expect to see in the coming years and suggestions for further research.
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2024 |
Hussain, G. |
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Journal Article |
From online hate speech to offline hate crime: the role of inflammatory language in forecasting violence against migrant and LGBT communities
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Social media messages often provide insights into offline behaviors. Although hate speech proliferates rapidly across social media platforms, it is rarely recognized as a cybercrime, even when it may be linked to offline hate crimes that typically involve physical violence. This paper aims to anticipate violent acts by analyzing online hate speech (hatred, toxicity, and sentiment) and comparing it to offline hate crime. The dataset for this preregistered study included social media posts from X (previously called Twitter) and Facebook and internal police records of hate crimes reported in Spain between 2016 and 2018. After conducting preliminary data analysis to check the moderate temporal correlation, we used time series analysis to develop computational models (VAR, GLMNet, and XGBTree) to predict four time periods of these rare events on a daily and weekly basis. Forty-eight models were run to forecast two types of offline hate crimes, those against migrants and those against the LGBT community. The best model for migrant crime achieved an R2 of 64%, while that for LGBT crime reached 53%. According to the best ML models, the weekly aggregations outperformed the daily aggregations, the national models outperformed those geolocated in Madrid, and those about migration were more effective than those about LGBT people. Moreover, toxic language outperformed hatred and sentiment analysis, Facebook posts were better predictors than tweets, and in most cases, speech temporally preceded crime. Although we do not make any claims about causation, we conclude that online inflammatory language could be a leading indicator for detecting potential hate crimes acts and that these models can have practical applications for preventing these crimes.
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2024 |
Arcila Calderón, C., Sánchez Holgado, P., Gómez, J., Barbosa, M., Qi, H., Matilla, A., Amado, P., Guzmán, A., López-Matías, D. and Fernández-Villazala, T. |
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