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This article is a study of mourning among Shi'a Muslims during the COVID-19 pandemic through a call-in talk show called #IAMHUSSEINI. By analyzing the discourses of callers and presenters and locating them within a visual context of the television studio, this article shows how the viewership of #IAMHUSSEINI constitutes a televisual majlis (Arabic: ‘assembly') composed of more than passive asynchronous consumption and resembling what Patrick Eisenlohr refers to as ‘atmospheres'. This article argues that the COVID-19 pandemic drove #IAMHUSSEINI to recalibrate to expectations of a spatially proximate ritual, rather than sustaining a ‘natively digital' aesthetic, repurposing Richard Rogers' approach to digital methods. This change brought about a tacit understanding of the televisual majlis among #IAMHUSSEINI's viewers. This article therefore posits a difference between ‘spatial intercorporeality', in which bodies are mediated by spatial proximity, and ‘functional intercorporeality’, in which they are mediated by the material preconditions of a shared activity.

Screenshots from the Telegram channels that I analyzed for my MA Thesis 'Vaccine Damages' and 'Lethal Injections': Strategic Communication in German Language Covid-19 Conspiracy Telegram Channel Screenshots were taken on February 10, 2022.

The COVID-19 pandemic generated (and keeps generating) a huge corpus of news articles, easily retrievable in Factiva with very targeted queries. This dataset, generated with an ad-hoc parser and NLP pipeline, analyzes the frequency of lemmas and named entities in news articles (in German, French, Italian and English ) regarding Switzerland and COVID-19. The analysis of large bodies of grey literature via text mining and computational linguistics is an increasingly frequent approach to understand the large-scale trends of specific topics. We used Factiva, a news monitoring and search engine developed and owned by Dow Jones, to gather and download all the news articles published between January 2020 and May 2021 on Covid-19 and Switzerland. Due to Factiva's copyright policy, it is not possible to share the original dataset with the exports of the articles' text; however, we can share the results of our work on the corpus. All the information relevant to reproduce the results is provided. Factiva allows a very granular definition of the queries, and moreover has access to full text articles published by the major media outlet of the world. The query has been defined as follows (syntax in bold, explanation in italics): ((coronavirus or Wuhan virus or corvid19 or corvid 19 or covid19 or covid 19 or ncov or novel coronavirus or sars) and (atleast3 coronavirus or atleast3 wuhan or atleast3 corvid* or atleast3 covid* or atleast3 ncov or atleast3 novel or atleast3 corona*)) Keywords for covid19; must appear at least 3 times in the text and ns=(gsars or gout) Subject is “novel coronaviruses” or “outbreaks and epidemics” and “general news” and la=X Language is X (DE, FR, IT, EN) and rst=tmnb Restrict to TMNB (major news and business publications) and wc>300 At least 300 words and date from 20191001 to 20212005 Date interval and re=SWITZ Region is Switzerland It is important to specify some details that characterize the query. The query is not limited to articles published by Swiss media, but to articles regarding Switzerland. The reason is simple: a Swiss user googling for “Schweiz Coronavirus” or for “Coronavirus Ticino” can easily find and read articles published by foreign media outlets (namely, German or Italian) on that topic. If the objective is capturing and describing the information trends to which people are exposed, this approach makes much more sense than limiting the analysis to articles published by Swiss media. Factiva’s field “NS” is a descriptor for the content of the article. “gsars” is defined in Factiva’s documentation as “All news on Severe Acute Respiratory Syndrome”, and “gout” as “The widespread occurrence of an infectious disease affecting many people or animals in a given population at the same time”; however, the way these descriptors are assigned to articles is not specified in the documentation. Finally, the query has been restricted to major news and business publications of at least 300 words. Duplicate check is performed by Factiva. Given the incredibly large amount of articles published on COVID-19, this (absolutely arbitrary) restriction allows retrieving a corpus that is both meaningful and manageable. metadata.xlsx contains information about the articles retrieved (strategy, amount) This work is part of the PubliCo research project. This work is part of the PubliCo research project, supported by the Swiss National Science Foundation (SNF). Project no. 31CA30_195905

The dataset comprises comments collected from the official Facebook page of the National Institute of Public Health of Kosovo (NIPHK) for a period of 6 months, from March 12 till August 31, 2020. On March 12, the first case of COVID-19 was confirmed in Kosovo. Comments were retrieved using a tool called Comment Exporter. These comments were in Albanian language and reflect the opinions of Kosovo citizens expressed on Facebook about the Covid-19 pandemics. This dataset contains a total of 10,132 comments along with 12 attributes. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

Dataset for the spatial econometric analysis of the change of greenhouse gas emissions during the Covid-19 pandemic (March-April 2020) for Southern Germany

COVID-2019 has been recognized as a global threat, and several studies are being conducted in order to contribute to the fight and prevention of this pandemic. This work presents a scholarly production dataset focused on COVID-19, providing an overview of scientific research activities, making it possible to identify countries, scientists and research groups most active in this task force to combat the coronavirus disease. The dataset is composed of 40,215 records of articles' metadata collected from Scopus, PubMed, arXiv and bioRxiv databases from January 2019 to July 2020. Those data were extracted by using the techniques of Python Web Scraping and preprocessed with Pandas Data Wrangling. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

Version 1.0 of the EXCEPTIUS project dataset (v.1.0) tracked all exceptional measures in the field of democratic governance/ human rights and international cooperation issued by national authorities in European Union (EU) countries (including UK and Switzerland, excluding Iceland) in order to tackle the COVID-19 pandemic from January to June 2020. The dataset also provides data on the implementation modalities of such measures. Version 2.0 now includes data on measures issued for subnational authorities (Austria, Belgium, Finland, France, Germany, Italy, Spain, Switzerland, UK) and covers the second (July- December 2020) and third (January-April 2021) waves. It also includes a new type event (10, emergency decision-making) allowing to distinguish between countries who implemented a state of emergency (type event 1) and countries which implemented emergency measures without activating state of emergency provisions.

The survey aimed to gather data on the impact of the COVID19 outbreak on the food support providers active in Greater Manchester. The lockdown created organizational hurdles to many services providing food to the most vulnerable. The survey explored more in depth the obstacles, the needs and the prospects of 55 organizations that were on the frontline in the first months of the crisis.