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      Media coverage, fake news, and the diffusion of xenophobic violence: A fine-grained county-level analysis of the geographic and temporal patterns of arson attacks during the German refugee crisis 2015–2017

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          Abstract

          Over the year of 2015, about 800.000 refugees arrived in Germany, a number which equals around one percent of the total population. This migration process was labelled the refugee crisis and was accompanied by a contested debate. On the one hand, there was a widespread willingness to voluntarily help arriving refugees, on the other hand, the number of xenophobic attacks against refugees drastically increased. Our paper will focus on a specific form of xenophobic violence with a strong symbolic meaning: We analyze how arson attacks against collective accommodation facilities spread. Using a comprehensive web chronicle, we collected temporal and spatial data about arson attacks perpetrated on accommodations or facilities for refugees in Germany between 2015 and 2017. We counted 251 attacks, assigned each incident location to its county, merged county characteristics such as population size, proportion of foreigners, right-wing party support, and—going beyond previous research—added geographically coded media data from two digital archives. Besides newspaper contents of a popular nation-wide tabloid, we use a data base that covers local fake news on refugees. Based on these data, we constructed a balanced panel data set with the counties as geographical units and periods of 14 days as the time dimension. Results indicate that social contagion drives the diffusion process of arson attacks. Spatial proximity of previous attacks increased the propensity of attacks in the neighboring counties. Attacks were more likely to occur in counties with larger populations and fewer foreigners. While local newspaper coverage did not impact the diffusion of xenophobic attacks, fake news were relevant–but only in East Germany. We also considered two particularly salient threatening events that received nation-wide media attention, namely Merkel’s “border opening” on the 5 th of September 2015 and the sexual assaults occurring during New Year’s 2015/16 in Cologne. Both were followed by temporary increases in violence.

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          The spread of true and false news online

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            Experimental evidence of massive-scale emotional contagion through social networks.

            Emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. Emotional contagion is well established in laboratory experiments, with people transferring positive and negative emotions to others. Data from a large real-world social network, collected over a 20-y period suggests that longer-lasting moods (e.g., depression, happiness) can be transferred through networks [Fowler JH, Christakis NA (2008) BMJ 337:a2338], although the results are controversial. In an experiment with people who use Facebook, we test whether emotional contagion occurs outside of in-person interaction between individuals by reducing the amount of emotional content in the News Feed. When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred. These results indicate that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale contagion via social networks. This work also suggests that, in contrast to prevailing assumptions, in-person interaction and nonverbal cues are not strictly necessary for emotional contagion, and that the observation of others' positive experiences constitutes a positive experience for people.
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              Social Media and Fake News in the 2016 Election

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: Writing – original draft
                Role: ConceptualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysis
                Role: Data curationRole: Formal analysis
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                20 July 2023
                2023
                : 18
                : 7
                : e0288645
                Affiliations
                [1 ] Sociology Department, University of Konstanz, Konstanz, Germany
                [2 ] AI Engineering, Schwarz IT KG, Neckarsulm, Germany
                [3 ] Program and Funding, Stifterverband, Berlin, Germany
                [4 ] ML Engineering, textada, University of Konstanz, Konstanz, Germany
                Caleb University, NIGERIA
                Author notes

                Competing Interests: NO authors have competing interests.

                Author information
                https://orcid.org/0000-0001-5240-2157
                Article
                PONE-D-22-32069
                10.1371/journal.pone.0288645
                10358929
                37471431
                ef0915a4-acff-4c4e-946f-f8c8cd3bfade
                © 2023 Hinz et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 22 November 2022
                : 1 July 2023
                Page count
                Figures: 3, Tables: 0, Pages: 23
                Funding
                Funded by: EXC 2117 Collective Behavior
                Award Recipient :
                TH is principal investigator of the EXC 2117 Collective Behavior at University of Konstanz, which supported collecting and arranging media data used in this paper.
                Categories
                Research Article
                People and Places
                Demography
                Refugees
                People and places
                Geographical locations
                Europe
                European Union
                Germany
                Social Sciences
                Economics
                Labor Economics
                Employment
                Unemployment Rates
                Social Sciences
                Economics
                Macroeconomics
                Unemployment Rates
                Social Sciences
                Economics
                Labor Economics
                People and Places
                Population Groupings
                Ethnicities
                European People
                German People
                Biology and Life Sciences
                Psychology
                Psychological Attitudes
                Social Sciences
                Psychology
                Psychological Attitudes
                Social Sciences
                Economics
                Human Capital
                Economics of Migration
                Social Sciences
                Sociology
                Communications
                Social Communication
                Social Media
                Computer and Information Sciences
                Network Analysis
                Social Networks
                Social Media
                Social Sciences
                Sociology
                Social Networks
                Social Media
                Custom metadata
                We have uploaded the complete data set used for analysis along with the respective stata code.

                Uncategorized
                Uncategorized

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