An Analytical Framework for Measuring Inequality in the Public Opinion on Policing—Assessing the Impacts of COVID-19 Pandemic Using Twitter Data — Oak Academic Publishing
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An Analytical Framework for Measuring Inequality in the Public Opinion on Policing—Assessing the Impacts of COVID-19 Pandemic Using Twitter Data
Crime and Well-Being Big Data Centre, Manchester Metropolitan University, Manchester, United Kingdom
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School of Science, Engineering and Environment, University of Salford, Salford, United Kingdom
1 Crime and Well-Being Big Data Centre, Manchester Metropolitan University, Manchester, United Kingdom
2 School of Science, Engineering and Environment, University of Salford, Salford, United Kingdom
As the COVID-19 pandemic sweeps across the globe, police forces are charged with new roles as they engage and enforce new policies and laws governing societal behaviours. However, how the police exercise these powers is an important factor in shaping public opinion and confidence concerning their activities across space and time. This research developed an analytical framework for measuring the inequality in the public opinion towards policing efforts during the pandemic using Twitter data. We demonstrate the utility of our framework using 3-months of tweets across 42 police force areas (Pfas) of England and Wales (UK). The results reveal that public opinions on policing is overwhelmingly negative across space and time, and that these opinions have been most exacerbated by the COVID-19 pandemic in three specific Pfas, namely Staffordshire, Thames Valley, and North Wales. We provided the link to the open-source script by which this research could be replicated and adapted to other study areas. This research has the potential to help law enforcement understand the dynamics of public confidence and trust in policing and facilitate action towards improved police services.
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