• COVID-19
• Publicationsclose
• Other research productsclose
• Closed Access close
• English close
• COVID-19 close
• Digital Humanities and Cultural Heritage close

Abstract In the last few years, the notion of applied history has seen a notable rise in interest among historians. Arising out of questions related to contemporary concerns, such as political extremism and Covid-19, several projects have taken up the challenge to address these questions and other issues by looking to the past, thereby furthering the idea that applied history warrants the attention of professional (academic) historians. The concept of applied history itself is, however, not new, begging questions of how these new projects use the term and how this usage relates to older definitions and methods associated with the term. This article shows that much of the most recent ‘wave’ of applied history has tended to present itself as closely related to history and policy, distinguishing itself by either drawing a hard line between public and applied history or by ignoring public history altogether. On the other hand, some have defined applied history as an approach or sub-field of public history, sometimes leading public historians to assume that these new groups are merely, and unhelpfully, putting a new logo on an old brand. This article offers a thorough overview of these contending developments and argues that the current conceptual and methodological confusion about applied history is detrimental to anyone relying on the term. Essentially, when a non-historian seeks the assistance of an applied historian and asks the logical question “and what do you do, exactly?,” the current uncertainty can result in major and off-putting confusion about what the term actually means.

The Velvet Light Trap gathered a diverse group of scholars with a range of specialties related to queer theory and media. This round-table touches on everything from dating apps to the films of John Waters to a livestreamed Indigo Girls concert, demonstrating the myriad ways digitality has affected queer media, representation, and audiences. The researchers began this discussion on 9 March 2020, only for closures due to the COVID-19 pandemic to begin in earnest a few days later. Thus, the participants' contributions began to reflect this fraught period toward the end of the conversation.

We report new data from a survey of loneliness in Australia during the Covid-19 lockdowns of 2020–21, in order to identify those age groups most at risk of increased loneliness. Counter-intuitively, proportionately fewer elderly Australians experienced increased loneliness as a result of lockdowns, as compared with 44% of those aged 19–29 and 31% of those aged 40–49. To explain this pattern, we investigated how lockdowns disturbed the complex connections between types of place affordance and the age-specific cultural scripts that normally give rise to a sense of belonging. For younger age groups, such scripts demand their identification with future orientations and a sense of belonging tied to the more distant and wide-ranging places of career advance, meeting, play, and pleasure that lockdown inhibited. By contrast, older retired cohorts were more inclined to frame their sense of belonging in the past through the maintenance of community connections and closer place-bonds of their locality, cultural places of memory and return that they were more happily confined to during lockdowns. Refereed/Peer-reviewed

Dr James Rogers explains how we can draw parallels between the current COVID-19 pandemic and the Second World War, particularly in how humans have responded to an extraordinary challenge.

In the past few months more than a billion people have faced restrictions unlike any seen before. Shops are closed; the death toll is rising; people across the globe have been forced to rise to an extraordinary challenge. But it is important to remember that humans have experienced pandemics before. In this documentary Dan Snow explores some of these previous pandemics and what they can teach us about Covid-19. He talks to Dr James Rogers about what lessons we can learn from WW2.

International audience

This edited volume investigates for the first time the impact of conspiracy theories upon the understanding of Europe as a geopolitical entity as well as an imagined political and cultural space. Focusing on recent developments, the individual chapters explore a range of conspiratorial positions related to Europe. In the current climate of fear and threat, new and old imaginaries of conspiracies such as Islamophobia and anti-Semitism have been mobilised. A dystopian or even apocalyptic image of Europe in terminal decline is evoked in Eastern European and particularly by Russian pro-Kremlin media, while the EU emerges as a screen upon which several narratives of conspiracy are projected trans-nationally, ranging from the Greek debt crisis to migration, Brexit and the COVID-19 pandemic. The methodological perspectives applied in this volume range from qualitative discourse and media analysis to quantitative social-psychological approaches, and there are a number of national and transnational case studies. This book will be of great interest to students and researchers of extremism, conspiracy theories and European politics.

This symposium brings together a range of Marxist perspectives on the state by both early career researchers and more established scholars I write this on day seven of a nation-wide police riot against anti-racist protests in the middle of a global pandemic during which the U S and U K states have failed to manage the outbreak of COVID-19, leading to the highest rate of unemployment since the Great Depression and tens of thousands of needless deaths And more is likely to unfold between now and publication These contributions were completed and submitted to Science & Society months ago Two of the contributions (Hunter and Munro) originally appeared in an earlier form in a series of blog posts "on the Marxist tradition of state dieory and its contemporary lineages," on die blog Legal Form, initiated by Chris O'Kane in 2019 So even diough the essays in this Symposium do not address recent events, diey nonetheless contain much that can help us understand the present situation This is powerful evidence of die enduring usefulness of Marxism and Marxist theories of the state

In this paper, we analyze and compare Croatian and Polish Twitter datasets. After collecting tweets related to COVID-19 in the period from 20.01.2020 until 01.07.2020, we automatically annotated positive, negative, and neutral tweets with a simple method, and then used a classifier to annotate the dataset again. To interpret the data, the total number as well as the number of positive and negative tweets are plotted through time for Croatian and Polish tweets. The positive/negative fluctuations in the visualizations are explained in the context of certain events, such as the lockdowns, Easter, and parliamentary elections. In the last step, we analyze tokens by extracting the most frequently occurring tokens in positive or negative tweets and calculating the positive to negative (and reverse) ratios.

Since December 2019, Covid-19 has been spreading rapidly across the world. Unsurprisingly, conversation in social networks about Covid-19 is increasing as well. The aim of this study is to identify tentative Covid-19 infection cases through social networks and, specifically, on Twitter, using machine learning techniques. Tweets were collected using the data set “Covid-19 Twitter”, between November 1, 2020 and December 30, 2020, and manually marked by the authors of this study as positive (describing a tentative Covid-19 infection case) or negative (pertaining to any other Covid-19 related issue) cases of Covid-19, creating a smaller but more focused dataset. This study was conducted in three phases: a. data collection and data cleaning, b. processing and analysis of tweets by machine learning techniques, and c. evaluation and qualitative/quantitative analysis of the achieved results. The implementation was based on Gradient Boosting Decision Trees, Support Vector Machines (SVM) and Deep Learning algorithms.