ABSTRACT
From the start of the COVID-19 pandemic in Germany, different groups have been protesting measures implemented by different government bodies in Germany to control the pandemic. It was widely claimed that many of the offline and online protests were driven by conspiracy narratives disseminated through groups and channels on the messenger app Telegram. We investigate this claim by measuring the frequency of conspiracy narratives in messages from open Telegram chat groups of the Querdenken movement, set up to organize protests against COVID-19 restrictions in Germany. We furthermore explore the content of these messages using topic modelling. To this end, we collected 822k text messages sent between April 2020 and May 2022 in 34 chat groups. By fine-tuning a Distilbert model, using self-annotated data, we find that 8.24% of the sent messages contain signs of conspiracy narratives. This number is not static, however, as the share of conspiracy messages grew while the overall number of messages shows a downward trend since its peak at the end of 2020. We further find a mix of known conspiracy narratives make up the topics in our topic model. Our findings suggest that the Querdenken movement is getting smaller over time, but its remaining members focus even more on conspiracy narratives. © 2022 Association for Computational Linguistics.
ABSTRACT
Face-to-face communication is important for building and maintaining relationships. The COVID-19 pandemic led to severe limitations in people's face-to-face interactions, resulting in most people relying more heavily on digital communication for social connection. Existing research has contributed to the understanding of how face-to-face communication is used alongside digital communication. However, we know little about what elements of face-to-face interactions people miss especially when in-person meetings are heavily reduced, and how this is related to their use of digital communication for social connection. In this study, we draw upon survey data that we collected in spring 2020 from a national sample of U. S. adults to answer these questions. We find that most people missed elements of face-to-face interactions and particularly valued spontaneous interactions, physical closeness, and independence from technology about in-person interactions. More frequent and increasing use of popular digital modes such as voice calls, video calls, text messages, and social media were all positively related to missing face-to-face communication. Our results contribute to the understanding of the role and value of in-person interactions in a digital world. © 2022, the authors. This work is licensed under the "Creative Commons Attribution – NonCommercial – NoDerivatives 4.0 International” license (CC BY-NC-ND 4.0).
ABSTRACT
Contact tracing for COVID-19 is especially challenging because transmission often occurs in the absence of symptoms and because a purported 20% of cases cause 80% of infections, resulting in a small risk of infection for some contacts and a high risk for others. Here, we introduce riskbased quarantine, a system for contact tracing where each cluster (a group of individuals with a common source of exposure) is observed for symptoms when tracing begins, and clusters that do not display them are released from quarantine. We show that, under our assumptions, risk-based quarantine reduces the amount of quarantine time served by more than 30%, while achieving a reduction in transmission similar to standard contact tracing policies where all contacts are quarantined for two weeks. We compare our proposed risk-based quarantine approach against test-driven release policies, which fail to achieve a comparable level of transmission reduction due to the inability of tests to detect exposed people who are not yet infectious but will eventually become so. Additionally, test-based release policies are expensive, limiting their effectiveness in low-resource environments, whereas the costs imposed by risk-based quarantine are primarily in terms of labor and organization.