Mediating Covid – Epidemic, Pandemic, Infodemic: A Project in Three Acts

Marc Hannappel, Viola Dombrowski, Matthias Kullbach, Institute of Sociology. Oul Han and Lukas Schmelzeisen, Institute for Web Science and Technologies. Universität Koblenz-Landau, Germany.

Prologue: Retrospect(ion)

On December 31st 2019, the World Health Organization (WHO) office in Beijing is informed of several cases of pneumonia of unknown origin. In the following days, similar cases with the same symptoms are being reported to the WHO. From January 11th onwards, the increasing evidence suggest that this could be the outbreak of a novel disease. On January 25th, the first cases in Europe are reported, followed by a first wave of measures, such as Lufthansa stopping nearly all flights to China, foreshadowing the political, economic, and public impact this outbreak will soon have globally.

By the end of February, more than one hundred cases are registered in Italy. From here onwards, the numbers will not only rapidly rise in Italy, but throughout Europe and increasingly in the rest of the world, finally leading the WHO to declare the outbreak of ‘SARS-nCov-2’ as a pandemic on March 11th. In turn, several European countries impose measures, restricting citizens’ freedom of movement to varying degrees. Alongside these tangible effects on the personal and professional lives of individuals – ourselves included – the closing of restaurants, shops and warehouses goes on to impact the (inter-)national economies greatly. Within just a few weeks, our research object has moved from ‘very far away’ to right at our doorsteps, now constituting the dominant topic worldwide for probably a long while.

Act 1: The project

Simultaneously with the spread of Covid-19, information, scientific insight and speculation have been spreading through different media. This leads us to form our research team, consisting of five scholars from four disciplines – sociology, political science, computer science, and management – from a seemingly safe distance in Germany on February 12th.

Identifying this outbreak as a risk event according to Keller [1], which is accompanied by an almost unprecedented media spectacle [2], we chose to look at three major German newspapers (BILD, Frankfurter Allgemeine Zeitung, Süddeutsche Zeitung), where a development of sheer mass in newspaper articles can be seen – in total as well as in relation to other reported topics (see Figures 1 and 2).

Furthermore, we chose to look at Twitter – representing discourse on social media platforms – where the novel Coronavirus is advancing to being a central topic, albeit in far greater variety than in the newspaper articles.

With the pandemic’s dynamic development, diverse discourses around Covid-19 are emerging and changing rapidly, leading our project to pursue the following goals:

1. Locating central topics and documenting their numerical development over time in both types of media (‘social’ and ‘traditional’).
2. Analysing structures of reciprocity between traditional media (BILD, FAZ, SZ), social networks (Twitter), as well as ‘fact producers’ (WHO), by using the results of the analysis conducted in 1, in order to find out where agendas are set in the discourses of mass media.
3. Examining in which ways the ‘objective’ course of the pandemic influences this fragmented discourse and, more importantly, which dynamics of their own they may develop.

Act 2: Theory

By ‘risk events’, we mean events that pose a threat to social groups and collectives, thereby breaking through routines and the self-evident nature of everyday life [1], making them extraordinary by default. Keller differentiates two types of risk events. The first type occurs in a shortened amount of time, posing a very immediate and palpable threat, such as natural or technological disasters, or the combination of both, like the Fukushima nuclear disaster. The second type, on the other hand, poses a less tangible threat that is not as immediate, for example climate change, which has been a point of public discourse for many decades now. Taking the Coronavirus crisis into consideration, we suggest looking at the two types of risk events as two ends of a highly contextual spectrum, as the events have not unexpectedly crept up on Europe as they have on the Chinese population. However, the individual perception of collective risk in both cases – which is a prerequisite for the classification as such – is highly dependent on the communication process surrounding these risk events and the way in which events are presented in media coverage. In a reciprocal motion, the reaction to this is then again incorporated into media reports [3]. While ‘the media’ transport information and pose as a platform for discourse, it is questionable if it is them that set the agendas of public discourse.

For studying the directions and mechanisms of influence that arise from the media, political elites, and the public opinion, agenda setting theory has been a key literature for the how and why of media salience of issues [4]. Most fundamentally, it has established the foundations of first- and second-level agenda setting by defining aspects around the salience of certain issues among the public (first level), followed by more detailed questions of which attributes are highlighted and why (second level). Due to the increasingly varied media landscape through the addition of online and social media, the agenda setting literature’s focus has shifted towards how the networked media agenda creates impact on the networked public agenda (third level).

Thus, the directions of agenda setting effects have spread into many branches of networks that disseminate, interpret, and modify information. The questions imposed by the second and third level of agenda setting, that of ‘how’ the Coronavirus crisis is discussed and through ‘which attributes and why’, are core questions due to the undisputable salience of the Coronavirus crisis, and it will be of importance for the construction of our methodological framework.

Act 3: Methodology

Following our research questions, we follow a mixed methods approach within the framework of an ‘explanatory sequential design’ [5]. In practice, we started out by web scraping, which is the automated extraction of text data from the web, to generate a corpus of data comprising all online articles from the German daily newspapers BILD, SZ and FAZ that have been published since December 31st, 2019 and contain the keyword ‘corona’. In addition, we collected all German tweets with the hashtags #corona, #coronavirus and #covid19. Despite the comparatively low number of users in Germany, Twitter is particularly interesting for the analysis of public discourse because it embodies a dynamic that is almost analogous to what Habermas describes as the public sphere, which is a network for the communication of content and statements: hence, opinions in which communication flows are filtered in such a way that they condense into topic-specific public opinions [6]. However, it would be naïve to regard Twitter as a possibility for the operationalisation of a general public. Neuman et al. point out that users of social media differ from the general (offline) population in terms of important socio-demographic characteristics [7]. Twitter can, however, be understood as a part of the public sphere, representing an important arena for discourse, and especially for the analysis of risk discourses [1], due to the open structures and possibilities for cross-platform discussion.

To gather insight into the reaction of public discourse as portrayed by traditional media and Twitter-discourses, we will conduct our analysis in three central interlocking steps:

1. Identifying key topics, and the time and intensity in which they appear for both traditional media and Twitter. For this, we use both frequency counts and algorithmic analysis methods, such as ‘topic modelling’ [8].
2. Determining which topics are set by which medium through time-dependent analysis.
3. Supplementing the distributional results of algorithmic analysis by employing interpretative methods, such as discourse analysis.

Epilogue: Prospects

When we started this project, we did not realise we would face this unique situation. Not only are we confronted with a mass of data – comprising more than 15,000 newspaper articles and more than two million tweets – we also find ourselves in a state of ‘domestic isolation’. Nevertheless, we want to continue our analyses, maybe with even more motivation for gaining a systematic overview of the situation – unfolding, past and present. Thus, we would like to conclude this ‘drama in three acts’ with an outlook and present the first interim results:

As seen in Figure 3, the reporting of German newspapers does not run parallel to the number of cases worldwide. Only when the disease reaches Europe, a continuous growth can be observed, strongly increasing with the acceleration of Covid-19 cases in Germany, and finally skyrocketing with the discussion of restrictions on public social life. This could suggest that a (perceived) increase in risk leads to an increase in public interest in a topic.

By focussing on topics of discussion, as well as the relation between the newspapers and Twitter, we can see that the discussions for many key topics apparently were initiated on Twitter, rather than in traditional media (see Figure 4). Following the agenda-setting theory, these distributions could be interpreted to suggest that traditional media react to Twitter news – meaning that the latter sets the agenda. Furthermore, we suspect that only isolated media reports regarding specific topics have led to major discussions on Twitter. However, we will only be able to gain deeper insight into this ‘hypothesis’, as well as the overall discourse, as we examine the data – with the help of selected topics – by implementing discourse analysis.

References

[1] Keller, R. (2011): Wissenssoziologische Diskursanalyse. Wiesbaden: VS Verlag.
[2] Kellner, D. (2018): Medienspektakel und Protest. In: Hoffmann, D.; Winter, R. (Eds.): Mediensoziologie. Baden-Baden: Nomos, 158-173.
[3] Schütz, H.; Wiedemann, P. M. (2003): Risikowahrnehmung in der Gesellschaft. Bundesgesundheitsblatt-Gesundheitsforschung. 7: 549-554.
[4] McCombs, M. E.; Shaw, D. L.; Weaver, D. H. (2014): New Directions in Agenda-Setting Theory and Research. Mass Communication and Society 17: 781-802.
[5] Schoonenboom, J.; Johnson, B. R. (2017): How to Construct a Mixed Methods Research Design. In: Baur, N.; Kelle, U.; Kuckartz, U. (Eds.): Mixed Methods. Wiesbaden: Springer VS, 107-131.
[6] Habermas, J. (2008): Faktizität und Geltung. Beiträge zur Diskurstheorie des Rechts und des demokratischen Rechtsstaats. Frankfurt a. M.: Suhrkamp.
[7] Neuman, R. W.; Guggenheim, L.; Hang, M. S.; Bae, S. Y. (2014): The Dynamics of Public Attention: Agenda-Setting Theory Meets Big Data. Journal of Communication. 64: 193-214.
[8] Stier, S.; Posch, L.; Bleier, A.; Strohmaier, M. (2017): When populists become popular: Comparing Facebook use by the right-wing movement Pegida and German political parties. Information, Communication & Society, 20(4): 1365-1388.

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