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This study aims to make the reader aware of recent changes in the white supremacist movement and how such changes have altered the ways in which the movement can be combatted.

The authors study the movement in two periods: from 1970 to 2005 and from 2006 onward. The authors contrast the two periods and discuss the legal and financial issues within each.

The authors find that while legal concepts such as vicarious liability and respondeat superior apply today just as they did before, new tools are needed to fight the new means of financing the movement.

The main limitation of this study is the lack of quantitative data. Because the “alt-right” became popular around 2015, there has not been enough time for the construction of detailed data sets.

While many law papers have explored the white supremacist movement, the financing side has gone under-analyzed in scholarly research. This is important in light of the rise of the internet, online payment processors, cryptocurrencies and remote organizing and fundraising.

The 2017 Charlottesville rally was organized and financed via podcasts, online forums, encrypted chats and anonymous payments. Since then, the movement has mostly gone underground and has become more violent and radical as many members have come to believe that marches and politics do not help them.

To the best of the authors’ knowledge, there are no papers in finance that deal extensively with this topic. The authors believe that the severity of the issue and the importance of its funding make this study a valuable source of information. The recent changes occurring within the movement are likely to become even more critical to its success or failure in the future.

In this article, the authors analyse the impact of the 2020 lockdown and the subsequent measures to contain the spread of COVID-19 in Italy in the hospitality industry by looking at the social demands brought forward by the restaurant sector.

To analyse social demands, the authors choose Twitter as an observation point using two hashtags as keywords to scratch the data: #iononriapro and #ioapro, which correspond to two different instances conveyed by the same subject: the restaurant sector. The instances linked to the hashtags produced different levels of engagement and penetration within the social structure and digital platform. To analyse the first block of data linked to the first hashtag-flag #iononriapro, the authors used content analysis. To analyse the second and third block of data linked to the hashtag-flag #ioapro, the authors used an automatic procedure, emotional text mining.

The analysis procedures allow us to reconstruct the positioning of the topics of closures and reopenings due to lockdown in this sector and to identify two explanatory dimensions: structural and affective, which explain the tension that has emerged between the State and the restaurant sector around COVID-related closures.

The study's findings not only contribute to the current understandings of the birth, transformation and penetration of social issues by the restaurant sector over the specific period linked to the COVID-19 pandemic and the measures imposed for its containment but are also valuable to analyse the dynamics through which Twitter hashtags and the social issues they represent find strength or lose interest in the public.

This paper aims to describe a letter written to undergraduate students before their enrollment in a required foundations course, Service-Learning in English Education, taken before admission to the English education program at [the university]. The course, offered in the spring of 2017, came on the heels of Donald Trump’s election to the US Presidency, an event that followed from a campaign that raged against “politically correct” social developments that respect the dignity of people historically marginalized in US society.

The letter lays out the perils of teaching a diversity-oriented course in an era of disdain for diverse people and cultures. The letter explains how the course design attempts to give all interpretive authority to the students through their selection of course books and the book club design of promoting discussion outside professorial surveillance.

The paper includes the comments of three students regarding their response to the letter and course, and concludes that teaching a politicized course in a tempestuous time is risky yet possible.

This paper looks at one teacher educator’s approach to introducing diversity-related ideas in a Red State during an anti-diversity presidency.

The current study has three main purposes: (1) replicate results from prior framing effects studies on social media. To do so, the study examines the influence of news frames (free speech vs. public order) on participants' attitudes toward an alt-right rally (2) expand prior research by examining the emotional reaction of participants to these frames and (3) probe the moderating effects of face-to-face heterogenous talk and heterogenous social media feeds.

Drawing from theoretical concepts such as competitive framing, emotions and heterogeneity, the study uses a randomized online experiment. The study examines a conversation in a Twitter thread that includes both free speech and public order frames in the comments to the thread. The total number of participants was 275.

The results show that free speech versus public order frame did not impact attitudes of the participants toward the alt-right rally. Findings also show the significant main effects of free speech and public order frames and the interaction of exposure to heterogeneity on emotional reactions of outrage and anger toward the alt-right rally. These findings suggest that framing research needs to take social media features into consideration for a complete picture of framing effects on social media.

Using a classic framing effects experiment, the study includes variables relevant to social media discussions on Twitter and examined the moderating effects of heterogeneity on emotional reactions. In addition, one of the important methodological contributions of the current study are the framing manipulations for an externally valid experimental design.

Planning an accelerated life test (ALT) for a product is an important task for reliability practitioners. Traditional methods to create an optimal design of an ALT are often computationally burdensome and numerically difficult. In this paper, the authors introduce a practical method to find an optimal design of experiments for ALTs by using simulation and empirical model building.

Instead of developing the Fisher information matrix-based objective function and analytic optimization, the authors suggest “experiments for experiments” approach to create optimal planning. The authors generate simulated data to evaluate the quantity of interest, e.g. 10th percentile of failure time and apply the response surface methodology (RSM) to find an optimal solution with respect to the design parameters, e.g. test conditions and test unit allocations. The authors illustrate their approach applied to the thermal ALT with right censoring and lognormal failure time distribution.

The design found by the proposed approach shows substantially improved statistical performance in terms of the standard error of estimates of 10th percentile of failure time. In addition, the approach provides useful insights about the sensitivity of each decision variable to the objective function.

More comprehensive experiments might be needed to test its scalability of the method.

This method is practically useful to find a reasonably efficient optimal ALT design. It can be applied to any quantities of interest and objective functions as long as those quantities can be computed from a set of simulated datasets.

This is a novel approach to create an optimal ALT design by using RSM and simulated data.

Gives examples of how to use WordPerfect version 5.1 to create spine labels, without having to purchase the CAT CD450 system. Provides instructions for choosing a label format; constructing the macros; and printing the labels.

The purpose of this paper is to examine the construction of Sweden as a racialised spatial imaginary in the emerging transnational networks of far-right media production. Departing from President Donald Trump’s widely reported remarks, in 2017, as to “what happened last night in Sweden”, it examines the racializing discourses through which Sweden is constructed as a dark future to be averted; a failed social experiment in immigration and multiculturalism symbolised by the “no-go zones” held to be dotted, yet denied, in its major cities. While the symbolic production of “problem areas” is a familiar dimension of the politics of immigration, the paper explores why Sweden-as-nation is so insistently and intimately associated with its putative no-go zones in what are termed the “revenge fantasies” of the far-right. Further, it argues that these modes of representation cannot be understood without examining the value of Sweden as a news commodity in the expansive far-right media environment.

The analysis offers the idea of “taboo news” to conceptualise putatively “alternative” news about Sweden which is confirmed through its denial in the mainstream.

It argues that examining the increasing importance of “taboo news” as a commodity form must be integrated into a reading of how these racializing narratives are produced and circulated.

In so doing, it examines the shaping of this racialised imaginary as a digital assemblage taking shape as a commodity in a newly emerging and under-researched field of communicative and ideological action.

Partisan news media, which often publish extremely biased, one-sided or even false news, are gaining popularity world-wide and represent a major societal issue. Due to a growing number of such media, a need for automatic detection approaches is of high demand. Automatic detection relies on various indicators (e.g. content characteristics) to identify new partisan media candidates and to predict their level of partisanship. The aim of the research is to investigate to a deeper extent whether it would be appropriate to rely on the hyperlinks as possible indicators for better automatic partisan news media detection.

The authors utilized hyperlink network analysis to study the hyperlinks of partisan and mainstream media. The dataset involved the hyperlinks of 18 mainstream media and 15 partisan media in Slovakia and Czech Republic. More than 171 million domain pairs of inbound and outbound hyperlinks of selected online news media were collected with Ahrefs tool, analyzed and visualized with Gephi software. Additionally, 300 articles covering COVID-19 from both types of media were selected for content analysis of hyperlinks to verify the reliability of quantitative analysis and to provide more detailed analysis.

The authors conclude that hyperlinks are reliable indicators of media affinity and linking patterns could contribute to partisan news detection. The authors found out that especially the incoming links with dofollow attribute to news websites are reliable indicators for assessing the type of media, as partisan media rarely receive links with dofollow attribute from mainstream media. The outgoing links are not such reliable indicators as both mainstream and partisan media link to mainstream sources similarly.

In contrast to the extensive amount of research aiming at fake news detection within a piece of text or multimedia content (e.g. news articles, social media posts), the authors shift to characterization of the whole news media. In addition, the authors did a geographical shift from more researched US-based media to so far under-researched European context, particularly Central Europe. The results and conclusions can serve as a guide how to derive new features for an automatic detection of possibly partisan news media by means of artificial intelligence (AI).

The peer review history for this article is available at the following link: https://publons.com/publon/10.1108/OIR-10-2020-0441.