An Analytical Framework for Measuring Inequality in the Public Opinions on Policing – Assessing the impacts of COVID-19 Pandemic using Twitter Data

M. Adepeju, Fatai Jimoh
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引用次数: 5

Abstract

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 are 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
衡量治安舆论不平等的分析框架——利用Twitter数据评估COVID-19大流行的影响
随着新冠肺炎疫情席卷全球,警察部队在参与和执行管理社会行为的新政策和法律时被赋予了新的角色。然而,警察如何行使这些权力是影响公众舆论和对其跨时空活动的信心的一个重要因素。这项研究开发了一个分析框架,用于使用推特数据衡量疫情期间公众舆论对警务工作的不平等。我们在英格兰和威尔士(英国)的42个警察辖区(PFA)使用了3个月的推文,展示了我们框架的实用性。研究结果显示,在不同的时间和空间内,公众对警务的看法都是负面的,而新冠肺炎疫情在三个特定的PFA(即斯塔福德郡、泰晤士河谷和北威尔士)最为严重。我们提供了开源脚本的链接,通过该链接可以复制这项研究并将其应用于其他研究领域。这项研究有可能帮助执法部门了解公众对警务的信心和信任动态,并促进改善警察服务的行动
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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