With the leverage of digital reproducibility, historical messages of hate are finding new recipients with breathtaking speed and scope. The rapid growth in popularity of right-wing extremist groups in response to transnational economic crises underscores the importance of examining in detail the language and political mobilization strategies of the New Right. In Europe, for example, populist right-wing activists organized around an anti-immigration agenda are becoming more vocal, providing pushback against the increase in migration flows from North Africa and Eastern Europe and countering support for integration with a categorical rejection of multiculturalism. In the United States, anti-immigration sentiment provides a rallying point for political and personal agendas that connect the rhetoric of borders with national, racial, and security issues. Digital Media Strategies of the Far Right in Europe and the United States is an effort to examine and understand these issues, informed by the conviction that an interdisciplinary and transnational approach can allow productive comparison of far-right propaganda strategies in Europe and the United States. With a special emphasis on performing ideology in the far-right music scene, on violent anti-immigrant stances, and on the far right's skillful creation and manipulation of virtual communities, the contributions foreground the cultural shibboleths that are exchanged among far-right supporters on the Internet, which serve to generate a sense of group belonging and the illusion of power far greater that the known numbers of neo-Nazis in any one country might suggest. Moreover, with attention to transatlantic right-wing movements and their use of particularly digital media, the essays in this volume put pressure on the similarities among the various national agents, while accommodating differences in the virtual and sometimes violent identities created and nurtured online.

"This book is. . . clear and well-written. . . anyone with any interest in the basis of quantitative analysis simply must read this book. . . . well-written, with a wealth of explanation. . ." --Dougal Hutchison in Educational Research Using real data examples, this volume shows how to apply bootstrapping when the underlying sampling distribution of a statistic cannot be assumed normal, as well as when the sampling distribution has no analytic solution. In addition, it discusses the advantages and limitations of four bootstrap confidence interval methods--normal approximation, percentile, bias-corrected percentile, and percentile-t. The book concludes with a convenient summary of how to apply this computer-intensive methodology using various available software packages.