Public Opinion

Social media exposes us to an incredible amount of information — from news stories to political messaging to pop culture. CSMaP studies how this information shapes public opinion and affects people’s political attitudes and beliefs.

Academic Research

  • Journal Article

    A Synthesis of Evidence for Policy from Behavioural Science During COVID-19

    • Kai Ruggeri, 
    • Friederike Stock, 
    • S. Alexander Haslam, 
    • Valerio Capraro, 
    • Paulo Boggio, 
    • Naomi Ellemers, 
    • Aleksandra Cichocka, 
    • Karen M. Douglas, 
    • David G. Rand, 
    • Sander van der Linden, 
    • Mina Cikara, 
    • Eli J. Finkel, 
    • James N. Druckman, 
    • Michael J. A. Wohl, 
    • Richard E. Petty, 
    • Joshua A. Tucker
    • Azim Shariff, 
    • Michele Gelfand, 
    • Dominic Packer, 
    • Jolanda Jetten, 
    • Paul A. M. Van Lange, 
    • Gordon Pennycook, 
    • Ellen Peters, 
    • Katherine Baicker, 
    • Alia Crum, 
    • Kim A. Weeden, 
    • Lucy Napper, 
    • Nassim Tabri, 
    • Jamil Zaki, 
    • Linda Skitka, 
    • Shinobu Kitayama, 
    • Dean Mobbs, 
    • Cass R. Sunstein, 
    • Sarah Ashcroft-Jones, 
    • Anna Louise Todsen, 
    • Ali Hajian, 
    • Sanne Verra, 
    • Vanessa Buehler, 
    • Maja Friedemann, 
    • Marlene Hecht, 
    • Rayyan S. Mobarak, 
    • Ralitsa Karakasheva, 
    • Markus R. Tünte, 
    • Siu Kit Yeung, 
    • R. Shayna Rosenbaum, 
    • Žan Lep, 
    • Yuki Yamada, 
    • Sa-kiera Tiarra Jolynn Hudson, 
    • Lucía Macchia, 
    • Irina Soboleva, 
    • Eugen Dimant, 
    • Sandra J. Geiger, 
    • Hannes Jarke, 
    • Tobias Wingen, 
    • Jana Berkessel, 
    • Silvana Mareva, 
    • Lucy McGill, 
    • Francesca Papa, 
    • Bojana Većkalov, 
    • Zeina Afif, 
    • Eike K. Buabang, 
    • Marna Landman, 
    • Felice Tavera, 
    • Jack L. Andrews, 
    • Aslı Bursalıoğlu, 
    • Zorana Zupan, 
    • Lisa Wagner, 
    • Joaquin Navajas, 
    • Marek Vranka, 
    • David Kasdan, 
    • Patricia Chen, 
    • Kathleen R. Hudson, 
    • Lindsay M. Novak, 
    • Paul Teas, 
    • Nikolay R. Rachev, 
    • Matteo M. Galizzi, 
    • Katherine L. Milkman, 
    • Marija Petrović, 
    • Jay J. Van Bavel
    • Robb Willer

    Nature, 2023

    View Article View abstract

    Scientific evidence regularly guides policy decisions, with behavioural science increasingly part of this process. In April 2020, an influential paper proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

    Date Posted

    Dec 13, 2023

    Tags

  • Book

    Computational Social Science for Policy and Quality of Democracy: Public Opinion, Hate Speech, Misinformation, and Foreign Influence Campaigns

    Handbook of Computational Social Science for Policy, 2023

    View Book View abstract

    The intersection of social media and politics is yet another realm in which Computational Social Science has a paramount role to play. In this review, I examine the questions that computational social scientists are attempting to answer – as well as the tools and methods they are developing to do so – in three areas where the rise of social media has led to concerns about the quality of democracy in the digital information era: online hate; misinformation; and foreign influence campaigns. I begin, however, by considering a precursor of these topics – and also a potential hope for social media to be able to positively impact the quality of democracy – by exploring attempts to measure public opinion online using Computational Social Science methods. In all four areas, computational social scientists have made great strides in providing information to policy makers and the public regarding the evolution of these very complex phenomena but in all cases could do more to inform public policy with better access to the necessary data; this point is discussed in more detail in the conclusion of the review.

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