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Article published In:
Language and Covid-19
Edited by Michaela Mahlberg and Gavin Brookes
[International Journal of Corpus Linguistics 26:4] 2021
► pp. 498–531

Communicating the unknown

An interdisciplinary annotation study of uncertainty in the coronavirus pandemic

ORCID logo | TU Darmstadt
ORCID logo | TU Darmstadt
ORCID logo | University of Melbourne
This paper presents an annotation approach to examine uncertainty in British and German newspaper articles on the coronavirus pandemic. We develop a tagset in an interdisciplinary team from corpus linguistics and sociology. After working out a gold standard on a pilot corpus, we apply the annotation to the entire corpus drawing on an “annotation-by-query” approach in CQPWeb, based on uncertainty constructions that have been extracted from the gold standard data. The annotated data are then evaluated and sociologically contextualised. On this basis, we study the development of uncertainty markers in the period under study and compare media discourses in Germany and the UK. Our findings reflect the different courses of the pandemic in Germany and the UK as well as the different political responses, media traditions and cultural concerns: While markers of fear are more important in British discourse, we see a steadily increasing level of disagreement in German discourse. Other forms of uncertainty such as ‘possibility’ or ‘probability’ are similarly frequent in both discourses.
Keywords: uncertainty, annotation, interdisciplinarity, Covid-19 discourse
Article outline
  • 1.Introduction
  • 2.Uncertainty in media discourses on COVID-19
    • 2.1Concepts of uncertainty
    • 2.2Linguistic uncertainty markers
  • 3.Methodology
    • 3.1Corpus and tools
    • 3.2Annotation scheme and gold standard development
    • 3.3Annotation by query: Extraction of constructions and operationalisation
      • 3.3.1Indications of personal uncertainty
        • Anxiety
        • Disagreement
        • Doubt
        • Ignorance
        • Presumption
      • 3.3.2Indications of situational uncertainty
        • Danger
        • Opportunity
        • Possibility
        • Probability
        • Vagueness
      • 3.3.3Operationalisation: CQL queries
  • 4.Results
    • 4.1Personal uncertainty markers
    • 4.2Situational uncertainty markers
  • 5.Conclusions
  • Acknowledgements
  • References
Published online: 23 August 2021
DOI logo
https://doi.org/10.1075/ijcl.21096.mul
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