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This study uses qualitative interpretive textual analysis of video games found on hate and extremist Web sites to explore the proliferation of these games on the Internet and the extent they advocate violence and conflict or portray hate groups in a positive way to existing and potential members. In particular, this study examines the “enemies” targeted in these games and the level of violence directed toward these enemies. Results indicate the majority of games examined promoted extreme violence and conflict toward blacks and Jewish people. The games analyzed in this study required the player to violently kill, wound, and maim minorities in order to advance and were often modified versions of classic video games in which the original enemies were replaced with religious, racial and ethnic minorities. This study suggests that video games found on hate and extremist sites are intended to indoctrinate players with white supremacist ideology and allow individuals who already hold racist ideologies to practice aggressive scripts toward minorities which may later influence real world interactions.

The Ku Klux Klan is the oldest and most well-known extremist group in the United States with a history dating back nearly 150 years. The Klan has been featured in numerous movies, books, documentaries, and been the center of countless news stories. But, in recent years, the Ku Klux Klan has been all but forgotten by researchers who believed the Klan was a dying organization with a nearly extinct membership of individuals who could not accept the end of segregation and the Klan‟s defeat during the Civil Rights Movement. But, recent research by the Southern Poverty Law Center shows the Klan is not extinct, nor is the Klan dying. Instead, the Ku Klux Klan is growing with new members joining across the country and the world. Research has shown the recent growth in membership has been caused by the election of the first black President of the United States, a poor economy and high unemployment, and an increase in the minority population of the United States brought on by immigration. In addition, research has suggested the growth in groups like the Ku Klux Klan has been caused by an increase in the number of Ku Klux Klan web sites on the Internet. This study used grounded theory and a mixed-method approach to examine the proliferation of Klan web sites and to achieve a better understanding of the Ku Klux Klan and its recent rise in membership. Using content analysis of current Klan web sites and in-depth interviews with current Klan leaders, this study examined the beliefs of the Ku Klux Klan, the purpose of the Ku Klux Klan in the 21st Century, why the Klan creates and maintains web sites, and examined the membership of the Ku Klux Klan. Based on analysis of Klan web sites and interviews with Klan leaders, Ku Klux Klan beliefs fall under two general themes. First, the Klan believes white Christians are held to a double standard and not allowed to have pride in their culture and heritage, while at the same time treated unfairly by the media, society, and the government. Second, the Klan believes in racial separation, and the need for whites to either remove themselves from a society perceived as against them or to combat that society through political and legal involvement. Results suggest the Klan creates web sites not for the sole purpose of recruit, but instead, to inform the general public of the Klan‟s goals to combat a double standard in society, and to market the Klan to greater segment of the American population, by using the Internet to rebrand the image of the Klan as an organization dedicated to preserving white, American, and Christian culture. In addition, results indicate no one group exists that can claim the title of “Ku Klux Klan.” Instead, this study found a variety of Klan organizations exist with competing ideologies and beliefs. Using a mixed-methods approach of incorporating quantitative and qualitative data, this study found two types of Klan organizations exist. One Klan is a traditional fraternal organization, while the other is a more radical and extremist organization intent on becoming a paramilitary organization, church or political party. Members of the Klan were generally observed to be average American citizens with families. More specifically, Klan members were revealed to be white, politically and religiously conservative Christians, many of whom were military veterans and owned their own business, and in general were opposed to a changing world and changing American society.

In an effort to better understand the risk of individuals being radicalised via the internet, this paper re-examines the phenomenon of online radicalisation by focusing on four considerations of interest: individual, online environment, interactions between individual and the online environment, and protective elements. A key premise of the discussion presented is that the different theoretical assumptions and linkages underlying each consideration are not only reconcilable but that together they provide a more comprehensive understanding of assessing risk of radicalisation via the internet than any perspective by itself. Implications for operationalising these four considerations and their associated factors to identify individuals at risk of being radicalised via the internet will also be discussed.

Common approaches to text categorization essentially rely either on n-gram counts or on word embeddings. This presents important difficulties in highly dynamic or quickly-interacting environments, where the appearance of new words and/or varied misspellings is the norm. A paradigmatic example of this situation is abusive online behavior, with social networks and media platforms struggling to effectively combat uncommon or nonblacklisted hate words. To better deal with these issues in those fast-paced environments, we propose using the error signal
of class-based language models as input to text classification algorithms. In particular, we train a next-character prediction model for any given class, and then exploit the error of such class-based models to inform a neural network classifier. This way, we shift from the ability to describe seen documents to the ability to predict unseen content. Preliminary studies using out-of-vocabulary splits from abusive tweet data show promising results, outperforming competitive text categorization strategies by 4–11%.

This report provides an overview of two seemingly new formations of online networks of accelerationist and neo-fascist entities that emerged in early 2021 and are self-described Atomwaffen Division spinoffs. It also provides an understanding of how they behave online and speaks to the threats of offline violence they pose.

VOX-Pol Blog post.