Coronavirus Discourses: Linguistic Evidence For Effective Public Health Messaging
- Funded by UK Research and Innovation (UKRI)
- Total publications:2 publications
Grant number: AH/V015125/1
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Key facts
Disease
COVID-19Start & end year
20212022Known Financial Commitments (USD)
$507,525.14Funder
UK Research and Innovation (UKRI)Principal Investigator
Svenja AdolphsResearch Location
United KingdomLead Research Institution
University of NottinghamResearch Priority Alignment
N/A
Research Category
Policies for public health, disease control & community resilience
Research Subcategory
Communication
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Minority communities unspecified
Occupations of Interest
Unspecified
Abstract
Developed in partnership with Public Health England, Public Health Wales and NHS Education for Scotland, this bid addresses key challenges that the coronavirus pandemic presents in relation to understanding the flow and impact of public health messages as reflected in public and private discourses. Our collaborators above who are charged with constructing effective public health messages have identified two particular challenges: messaging around geographical borders (e.g. between England and Wales, and in local lockdowns) and messaging aimed at BAME populations. These areas will be the focus of our research, and we will deliver benefits to our collaborators in the form of initial analytical results and discussion from month 2 onwards. As human behaviour is shaped by the reception and production of discourse, and by the reasoning about different sources of information, we propose a new approach to track the trajectories of public health messages once they are released to the public. Moving beyond corpus linguistic approaches that focus on language production, we will investigate the complex relationship between the production and the reception of discourses relating to specific types of public health messages, focusing on linguistic patterns (in particular modality and stance markers). Drawing on our track record in the construction and analysis of heterogenous corpora and our ongoing work on privacy enhancing technologies, we propose to carry out the first large scale analysis of the trajectories of public health messages relating to the coronavirus pandemic in the UK.
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