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The advent of the Internet inadvertently augmented the functioning and success of violent extremist organizations. Terrorist organizations like the Islamic State in Iraq and Syria (ISIS) use the Internet to project their message to a global audience. The majority of research and practice on web‐based terrorist propaganda uses human coders to classify content, raising serious concerns such as burnout, mental stress, and reliability of the coded data. More recently, technology platforms and researchers have started to examine the online content using automated classification procedures. However, there are questions about the robustness of automated procedures, given insufficient research comparing and contextualizing the difference between human and machine coding. This article compares output of three text analytics packages with that of human coders on a sample of one hundred nonindexed web pages associated with ISIS. We find that prevalent topics (e.g., holy war) are accurately detected by the three packages whereas nuanced concepts (Lone Wolf attacks) are generally missed. Our findings suggest that naïve approaches of standard applications do not approximate human understanding, and therefore consumption, of radicalizing content. Before radicalizing content can be automatically detected, we need a closer approximation to human understanding.

This research examines the relationship between race and exposure to online hate material. The utilization of websites, weblogs, newsgroups, online games, radio broadcasts, online newsletters and a myriad of other online platforms has proliferated race-based hate groups in the US (Shafer 2002). According to the Southern Poverty Law Center (SPLC), the number of hate groups has been on the rise since the 1990s and continues to gain momentum with the advent of social media (Potok 2017). Exposure to separatist ideologies has propelled these radical rightwing groups into the mainstream by way of social media platforms, as they are “the most active producers of online hate material” (Costello, Hawdon, Ratliff, and Grantham 2016: pg. 313). That dissemination of radical rightwing ideologies, such as white supremacy, racial purity, and racial solidarity, exists is not enough in understanding what individuals are exposed to race-based hate ideologies in online platforms. Exposure is the key to understanding the growth of these race-based hate groups and ways of countering the efforts to disseminate radical rightwing ideologies due to its relationship to hate group emergence and persistence. More so, understanding how these groups target individuals and recruit through social networking sites can provide insight into exposure. Exposure to hate material aids groups in recruiting new members and victimizing potential targets. In the same manner, exposure to hate material is victimization of those who are exposed. In a sample collected by Costello et al. (2016a), of those exposed to hate material online nearly half centered on race. Thus, it is tantamount that research is conducted examining the role that race plays in determining who is exposed to hate material online, and how individuals react to hate material based on race. This dissertation will examine the importance of exposure to hate. Specifically, this dissertation will analyze survey data gathered from the Online Extremism Survey using logistic regression analysis and linear regression to understand exposure to hate material online and routine activity theory.

This study focuses on the role of Internet memes in the communication of two far-right groups in Finland. The material consists of 426 memes posted by Finland First and the Soldiers of Odin between the years 2015 and 2017 on Facebook. Multimodal discourse analysis was applied to understand the contents, forms, and rhetorical functions communicated via the Internet memes. The analysis shows that the contents of the memes revolve around six themes: history, humor, mythology, symbols, news and mottos. By using Internet memes, the groups aim to construe a heroic imagined past, to lend legitimacy to the nationalist cause, to arouse moral anger and hate toward refugees, and to encourage the movements’ followers to fight. We argue that, for the extreme groups, Internet memes are tools to crystallize their arguments in an easily shareable and concise form, which makes the memes useful tools in persuasion and mobilization, as well as attracting new audiences.

As demonstrated by the 2016 presidential election, memes have become the suasory tactic par excellence for the promotional and recruitment efforts of the Alt-right. Memes are not simply humorous shorthands or pithy assertions, but play a significant role in the machinations of politics and how the public comes to understand and respond to their government and compatriots. Using the tools of rhetorical criticism, the authors detail how memetic persuasion operates, with a particular focus on the 2016 election of Donald J. Trump. Make America Meme Again reveals the rhetorical principles used to design Alt-right memes, outlining the myriad ways memes lure mainstream audiences to a number of extremist claims. In particular, this book argues that Alt-right memes impact the culture of digital boards and broader public culture by stultifying discourse, thereby shaping how publics congeal. The authors demonstrate that memes are a mechanism that proliferate white nationalism and exclusionary politics by spreading algorithmically through network cultures in ways that are often difficult to discern. Alt-right memes thus present a significant threat to democratic praxis, one that can begin to be combatted through a rigorous rhetorical analysis of their power and influence. Make America Meme Again illuminates the function of networked persuasion for scholars and practitioners of rhetoric, media, and communication; political theorists; digital humanists; and anyone who has ever seen, crafted, or proliferated a meme.

VOX-Pol Blog Post.

VOX-Pol Blog post.