Abstract
In recent years behavioural science has quickly become embedded in national level governance. As the contributions of behavioural science to the UK's COVID-19 response policies in early 2020 became apparent, a debate emerged in the British media about its involvement. This served as a unique opportunity to capture public discourse and representation of behavioural science in a fast-track, high-stake context. We aimed at identifying elements which foster and detract from trust and credibility in emergent scientific contributions to policy making. With this in mind, in Study 1 we use corpus linguistics and network analysis to map the narrative around the key behavioural science actors and concepts which were discussed in the 647 news articles extracted from the 15 most read British newspapers over the 12-week period surrounding the first hard UK lockdown of 2020. We report and discuss (1) the salience of key concepts and actors as the debate unfolded, (2) quantified changes in the polarity of the sentiment expressed toward them and their policy application contexts, and (3) patterns of co-occurrence via network analyses. To establish public discourse surrounding identified themes, in Study 2 we investigate how salience and sentiment of key themes and relations to policy were discussed in original Twitter chatter (N = 2,187). In Study 3, we complement these findings with a qualitative analysis of the subset of news articles which contained the most extreme sentiments (N = 111), providing an in-depth perspective of sentiments and discourse developed around keywords, as either promoting or undermining their credibility in, and trust toward behaviourally informed policy. We discuss our findings in light of the integration of behavioural science in national policy making under emergency constraints.
Highlights
Public trust in the transparency and reliability of scientific evidence is an important component of effective responses to major challenges and crises (Hendriks et al, 2015; Pittinsky, 2015)
We find that increased salience can be linked to divisiveness in sentiment, associated with a cluster between Behavioural Insights Team and Halpern coupled with policy application of behavioural science in the first wave
This analysis does not tell us how the public responded to these articles. To identify whether such stories gained traction on social media, we identified a set of publicly available Twitter data to track the keywords identified in Study 1
Summary
Public trust in the transparency and reliability of scientific evidence is an important component of effective responses to major challenges and crises (Hendriks et al, 2015; Pittinsky, 2015). In Study 1, we looked at patterns of salience and sentiment toward behavioural science in newspaper articles over the 24week period surrounding the first UK lockdown of 2020 This analysis does not tell us how the public responded to these articles. Twitter is popular for capturing public perceptions with over 330 million registered global users who dynamically generate over 500 million messages ( called “tweets”) per day (Chae, 2015; Mention, 2018) We opted for this (as opposed to another) social media platform for: (1) Twitter’s informal, colloquially generated and unconstrained opinion data (Fried et al, 2014; Moe and Schweidel, 2017), (2) Twitter’s ability to attract individuals focused on information sharing and seeking (Hughes et al, 2012). We reasoned that mapping the salience and sentiments of the identified behavioural science concepts and actors from Study 1 over the same time period in this dataset, would allow us to identify the nature and extent of concordance of public opinion in line with that expressed in print media
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