To investigate how people form their identity on social networks and control the impressions they invoke in their audiences, we analyzed personal profiles of 50 university student Facebook users using Erving Gofmann´s dramaturgical theory. We identified five basic forms through which users create and present their identities: The Public diary, The Influencer, The Entertainer, Job and education and Hobby, as well as the appropriate secondary roles performed by users who interact with them.These findings are corroborated by 8 semi-structured interviews with respondents, which enable a more in-depth exploration of the way they use Facebook, the social interactions they participate in, their motivation for posting contributions, and how they engage in impression management, perceive privacy and resolve issues caused by multiple audiences.A better understanding of how privacy is conceived and what motivates users to share their personal information online is essential for public authorities’ cooperation on shaping company privacy policies and creation of appropriate legal regulations.The key results confirm the presence of conscious effort to make a desired impression and prove Goffman’s theory of face-to-face interactions to be relevant in the context of online social networks.
Computational methods offer a new perspective on the evolving agendas of right-wing movements and parties online. This article showcases computational approaches to text analysis (specifically so-called topic models) to diachronically investigate nativist right-wing issues in social media by comparing comments posted on the Facebook page of the Pegida movement to those of the Alternative for Germany. After describing topic modelling as an increasingly popular method and drawing on the literature on right-wing nativism online, we investigate a set of shared issues relevant to the mobilization of commentators, including opposition to Islam, migration, the government and the media. We furthermore show contrastively how issue prevalence differs between the two groups, and how issue shares change over time, in some instances converging on a shared nativist core. We close with a series of suggestions on the utility of computation content analysis for the study of rapidly evolving political agendas.
Running across the globe for nearly 2 years, the Covid-19 pandemic keeps demonstrating its strength. Despite a lot of understanding, uncertainty regarding the efficiency of interventions still persists. We developed an age-structured epidemic model parameterized with epidemiological and sociological data for the first Covid-19 wave in the Czech Republic and found that (1) starting the spring 2020 lockdown 4 days earlier might prevent half of the confirmed cases by the end of lockdown period, (2) personal protective measures such as face masks appear more effective than just a realized reduction in social contacts, (3) the strategy of sheltering just the elderly is not at all effective, and (4) leaving schools open is a risky strategy. Despite vaccination programs, evidence-based choice and timing of non-pharmaceutical interventions remains an effective weapon against the Covid-19 pandemic.
This report presents a technical description of our agent-based epidemic model of a particular middle-sized municipality. We have developed a realistic model with 56 thousand inhabitants and 2.7 million of social contacts. These form a multi-layer social network that serves as a base of our epidemic simulation. The disease is modeled by our extended SEIR model with parameters fitted to real epidemics data for Czech Republic. The model is able to simulate a whole range of non-pharmaceutical interventions on individual level, such as protective measures and physical distancing, testing, contact tracing, isolation and quarantine. The effect of government-issued measures such as contact restrictions in different environments (schools, restaurants, vendors, etc.) can also be simulated. The model is implemented in Python and is available as open source at: www.github.com/epicity-cz/model-m/releases
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