Online Library

Policymakers have recently expressed concerns over the role of recommendation algorithms and their role in forming “filter bubbles”. This is a particularly prescient concern in the context of extremist content online; these algorithms may promote extremist content at the expense of more moderate voices. In this article, we make two contributions to this debate. Firstly, we provide a novel empirical analysis of three platforms’ recommendation systems when interacting with far-right content. We find that one platform—YouTube—does amplify extreme and fringe content, while two—Reddit and Gab—do not. Secondly, we contextualise these findings into the regulatory debate. There are currently few policy instruments for dealing with algorithmic amplification, and those that do exist largely focus on transparency. We argue that policymakers have yet to fully understand the problems inherent in “de-amplifying” legal, borderline content and argue that a co-regulatory approach may offer a route towards tackling many of these challenges.

In this paper we examine how offline protests attended by members of the Australian far-right shape online interactions. Tweets about the 2019 St Kilda beach rally were collected. Users were manually classified as supporters (n = 104) or opponents of the rally (n = 872). Network analysis demonstrated that interactions between the two groups increased at the time of the rally. Natural language processing showed that both groups became angrier and used more “othering” language during the rally. However, there were stark differences in the moral worldviews, highlighting the very different moral positions that underpin engagement with, and opposition to, the far-right agenda.

Der Rechtsterrorismus ist im digitalen Zeitalter angekommen. Von Christchurch bis El Paso haben sich neue Ausdrucksformen rechter Gewalt etabliert, deren Täter mehr in digitalen Subkulturen als in rechtsextremen Organisationen zu verorten sind. Die radikalisierenden Tendenzen obskurer Online-Communitys geraten somit stärker in den Fokus der Forschung und fordern das Verständnis von rechtem Terror heraus. Wie verändert sich der Rechtsterrorismus also im digitalen Zeitalter? Mit diesem Beitrag möchten wir diese Frage mit dem Verweis auf die Beziehung von digitalen Hasskulturen und rechtsterroristischer Gewalt beleuchten. Wir argumentieren, dass die Analyse der Gewalttaten nicht ohne das Verständnis digitaler Hasskulturen auskommt, die Menschenfeindlichkeit über ironische Kommunikationsformate normalisiert. Aus ihnen heraus bildet sich eine rechtsterroristische Subkultur, die die ambivalenten Erzeugnisse digitaler Kulturen aufgreift und mit gewaltverherrlichenden Inhalten des Neonazismus verbindet, um eines zu erreichen: Menschen zur Gewalt anzuspornen.

This report represents a first contribution by the Samir Kassir Foundation (SKF) to the ongoing and growing debate on the role of communication in the radicalisation process and the mechanisms to prevent or counter violent extremism (CVE). The primary focus of this research is communication by and about the Islamic State and did not include communication by and about militant Islamist organisations from other ideological and sectarian backgrounds. It is based on qualitative opinion and media consumption research conducted in February and March 2016 with Lebanese audiences in Tripoli, North Lebanon, West Bekaa and among Syrian refugees with the support of the Ministry of Foreign Affairs of the Netherlands under contract No. 28141. The project was implemented by a steering committee led by academic and policy consultant Drew Mikhael and comprised of SKF Executive Director Ayman Mhanna, SKF Programs Coordinator Nassim AbiGhanem, academic and senior researcher Nidal Ayoub and social media communication specialist Marie-Thérèse Corbani. The contents of this report are the sole responsibility of the Samir Kassir Foundation and can in no way be taken to reflect the views of the Ministry of Foreign Affairs of the Netherlands

VOX-Pol Blog post.

This paper presents a dataset with over 3.3M threads and 134.5M posts from the Politically Incorrect board (/pol/) of the imageboard forum 4chan, posted over a period of almost 3.5 years (June 2016-November 2019). To the best of our knowledge, this represents the largest publicly available 4chan dataset, providing the community with an archive of posts that have been permanently deleted from 4chan and are otherwise inaccessible. We augment the data with a few set of additional labels, including toxicity scores and the named entities mentioned in each post. We also present a statistical analysis of the dataset, providing an overview of what researchers interested in using it can expect, as well as a simple content analysis, shedding light on the most prominent discussion topics, the most popular entities mentioned, and the level of toxicity in each post. Overall, we are confident that our work will further motivate and assist researchers in studying and understanding 4chan as well as its role on the greater Web. For instance, we hope this dataset may be used for cross-platform studies of social media, as well as being useful for other types of research like natural language processing. Finally, our dataset can assist qualitative work focusing on in-depth case studies of specific narratives, events, or social theories.