Online Library

YouTube is by far the largest host of user-generated video content worldwide. Alas, the platform also hosts inappropriate, toxic, and/or hateful content. One community that has come into the spotlight for sharing and publishing hateful content are the so-called Involuntary Celibates (Incels), a loosely defined movement ostensibly focusing on men’s issues, who have often been linked to misogynistic views. In this paper, we set out to analyze the Incel community on YouTube. We collect videos shared on Incel-related communities within Reddit, and perform a data-driven characterization of the content posted on YouTube along several axes. Among other things, we find that the Incel community on YouTube is growing rapidly, that they post a substantial number of negative comments, and that they discuss a broad range of topics ranging from ideology, e.g., around the Men Going Their Own Way movement, to discussions filled with racism and/or misogyny. Finally, we quantify the probability that a user will encounter an Incel-related video by virtue of YouTube’s recommendation algorithm. Within five hops when starting from a non-Incel-related video, this probability is 1 in 5, which is alarmingly high given the toxicity of said content.

Exploring the cases of India and Ethiopia, this article develops the concept of “extreme speech” to critically analyze the cultures of vitriolic exchange on Internet-enabled media. While online abuse is largely understood as “hate speech,” we make two interventions to problematize the presuppositions of this widely invoked concept. First, extreme speech emphasizes the need to contextualize online debate with an attention to user practices and particular histories of speech cultures. Second, related to context, is the ambiguity of online vitriol, which defies a simple antonymous conception of hate speech versus acceptable speech. The article advances this analysis using the approach of “comparative practice,” which, we suggest, complicates the discourse of Internet “risk” increasingly invoked to legitimate online speech restrictions.

Elizabeth T. Harwood on networks of provocation.

This article examines the forms and feelings of togetherness evident in both Manchester city centre and on social media during the first anniversary of the 22 May 2017 Manchester Arena bombing. To do this, we introduce a conceptual framework that conceives commemorative public atmospheres as composed of a combination of ‘more or less digital’ elements. We also present a methodological approach that combines the computational collection and analysis of Twitter content with short-term team autoethnography. First, the article addresses the concept of public atmospheres before introducing the case study and outlining our methodology. We then analyse the shifting moods of togetherness created by the official programme of commemorative events known as Manchester Together and their digital mediatisation through Twitter. We then explore a grassroots initiative, #LoveMCRBees, and how it relied on the materialisation of social media logics to connect people. Overall, we demonstrate how public atmospheres, as constituted in more and less digital ways, provide a framework for conceptualising commemorative events, and how togetherness is reworked by social media, especially in the context of responses to terrorism.

Recent acts of terrorism and hate crimes have prompted a renewed focus on the possible links between internet content and offline violence. While some have focused on the role that social media companies play in moderating user-generated content, others have called for Congress to pass laws regulating online content promoting terrorism or violence. Proposals related to government action of this nature raise significant free speech questions, including (1) the reach of the First Amendment’s protections when it comes to foreign nationals posting online content from abroad; (2) the scope of so-called “unprotected” categories of speech developed long before the advent of the internet; and (3) the judicial standards that limit how the government can craft or enforce laws to preserve national security and prevent violence.

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.