The Effects of Corona on the German Public Discourse in Online Newspapers and Twitter and its Mediated Development Over 2019-2020

Beginning with several reports of pneumonia of unknown origin to the Chinese branch of the World Health Organisation in Beijing on December 31st of 2019, a worldwide discourse ensued about what was later identified by Chinese officials as a new type of the Corona Virus, which had previously gained notoriety during the SARS outbreak in 2002/2003. This has also sparked public debate in Germany, following initial articles about a ‘mysterious pulmonary disease’ on December 31st in two of the largest daily newspapers of the country: BILD-Zeitung and Süddeutsche Zeitung. While this initial coverage by traditional media outlets follows a sober tone that is especially surprising for the right-leaning BILD-Zeitung, a transformation in discourse appears two weeks after the outbreak on January 14th of 2020. From this moment on, larger newspapers report multiple times a day about different aspects of the epidemic: origin, progression, possible methods of prevention, economic consequences, and more. Simultaneously, a more controversial and evidently more diverse discourse takes place on social media, such as Twitter. On the one side, actors deliberate in accordance with the tone of the newspapers: comparing the new outbreak to the common influenza, pushing towards a more ‘pragmatic’ stance, putting developments into perspective. In contrast, the online sphere also offers an alternative spectrum of interpretations and argumentations: claims of a much higher mortality rate than published by officials, conspiracy-like speculations about a synthetic origin of the virus, or rumors about the virus having originally escaped from a laboratory. Our paper therefore identifies the various arguments in the discourse and analyzes the interpretative frames. By doing so, it contributes to the theoretical background of prior studies that observe social media’s challenger against traditional media during crisis times. To this aim, we capture how the ‘crisis’ of a possible global pandemic impacts the public discourse on comparative levels of media. In order to reach both qualitative depth and quantitative breadth, we implement a unique set of mixed methods by integrating classical content analysis, quantitative text analysis, and computational social science. Firstly, we will utilize an iterative keyword-selection method between data retrieval and content analysis in order to collect the Twitter data. Then we will map the discursive structure through the computational analysis of keywords, hashtags, and users, which we use to retroactively identify pivotal points of the pandemic. Finally, in order to prevent misinterpretation about the transformation of discourse, we validate results with a sociological discourse analysis. All findings will be interpreted together and embedded into a theoretical framework.