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Details of Grant 

EPSRC Reference: EP/W011212/1
Title: XAIvsDisinfo: eXplainable AI Methods for Categorisation and Analysis of COVID-19 Vaccine Disinformation and Online Debates
Principal Investigator: Bontcheva, Professor K
Other Investigators:
Scarton, Dr C
Researcher Co-Investigators:
Project Partners:
Department: Computer Science
Organisation: University of Sheffield
Scheme: Standard Research
Starts: 01 July 2021 Ends: 31 December 2022 Value (£): 233,177
EPSRC Research Topic Classifications:
Artificial Intelligence
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:  
Summary on Grant Application Form
UK vaccination rates are in decline and experts believe that vaccine disinformation, widely spread

in social media, may be one of the reasons. Recent surveys have established that vaccine

disinformation is impacting negatively citizen trust in COVID-19 vaccination specifically. As a

response, the UK Government agreed with Twitter, Facebook, and YouTube measures to limit the

spread of disinformation. However, simply removing disinformation from platforms is not enough,

as the government also needs to monitor and respond to the concerns of vaccine hesitant citizens.

Moreover, manual detection and tracking of disinformation, as currently practiced by many

journalists, is infeasible, given the scale of social media.

XAIvsDinfo aims to address these gaps through novel research on explainable AI-based models for

large-scale analysis of vaccine disinformation. Specifically, vaccine disinformation will be classified

automatically into the six narrative types defined by First Draft. A second model will categorise

vaccine statements as pro-vaccine, anti-vaccine, vaccine-hesitant, or other.

We will investigate explainable machine learning approaches that are human interpretable: both

in detecting errors and weaknesses of the models and in providing human-readable explanations

of the models' decisions.

XAIvsDisinfo will also create two new multi-platform datasets and organise a new community

research challenge on cross-platform analysis of vaccine disinformation, as follow-up from our

RumourEval one.

Our XAI models and tools will be integrated into the open-source InVID-WeVerify plugin, for take

up by journalists and fact-checkers. The project outputs will also contribute to evidence-based

policy activities by the UK government on improving citizen perception of COVID-19 vaccines.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
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Further Information:  
Organisation Website: http://www.shef.ac.uk