Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = −0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.

Rising political polarization is, in part, attributed to the fragmentation of news media and the spread of misinformation on social media. Previous reviews have yet to assess the full breadth of research on media and polarization. We systematically examine 94 articles (121 studies) that assess the role of (social) media in shaping political polarization. Using quantitative and qualitative approaches, we find an increase in research over the past 10 years and consistently find that pro-attitudinal media exacerbates polarization. We find a hyperfocus on analyses of Twitter and American samples and a lack of research exploring ways (social) media can depolarize. Additionally, we find ideological and affective polarization are not clearly defined, nor consistently measured. Recommendations for future research are provided.

Both liberals and conservatives believe that using facts in political discussions helps to foster mutual respect, but 15 studies—across multiple methodologies and issues—show that these beliefs are mistaken. Political opponents respect moral beliefs more when they are supported by personal experiences, not facts. The respect-inducing power of personal experiences is revealed by survey studies across various political topics, a field study of conversations about guns, an analysis of YouTube comments from abortion opinion videos, and an archival analysis of 137 interview transcripts from Fox News and CNN. The personal experiences most likely to encourage respect from opponents are issue-relevant and involve harm. Mediation analyses reveal that these harm-related personal experiences increase respect by increasing perceptions of rationality: everyone can appreciate that avoiding harm is rational, even in people who hold different beliefs about guns, taxes, immigration, and the environment. Studies show that people believe in the truth of both facts and personal experiences in nonmoral disagreement; however, in moral disagreements, subjective experiences seem truer (i.e., are doubted less) than objective facts. These results provide a concrete demonstration of how to bridge moral divides while also revealing how our intuitions can lead us astray. Stretching back to the Enlightenment, philosophers and scientists have privileged objective facts over experiences in the pursuit of truth. However, furnishing perceptions of truth within moral disagreements is better accomplished by sharing subjective experiences, not by providing facts.

We present a novel approach to automatically identify driver behaviors from vehicle trajectories and use them for safe navigation of autonomous vehicles. We propose a novel set of features that can be easily extracted from car trajectories. We derive a data-driven mapping between these features and six driver behaviors using an elaborate web-based user study. We also compute a summarized score indicating a level of awareness that is needed while driving next to other vehicles. We also incorporate our algorithm into a vehicle navigation simulation system and demonstrate its benefits in terms of safer real-time navigation, while driving next to aggressive or dangerous drivers.There has been a wide range of work studying drivers' behaviors in Social Psychology and Transportation. Feng et al. [2] proposed five driver characteristics (age, gender, year of driving experience, personality via blood test, and education level) and four environmental factors (weather, traffic situation, quality of road infrastructure, and other cars' behavior), and mapped them to 3 levels of aggressiveness (driving safely, verbally

Deep partisan conflict in the mass public threatens the stability of American democracy. We conducted a megastudy (n=32,059) testing 25 interventions designed by academics and practitioners to reduce Americans’ partisan animosity and anti-democratic attitudes. We find nearly every intervention reduced partisan animosity, most strongly by highlighting sympathetic and relatable individuals with different political beliefs. We also identify several interventions that reduced support for undemocratic practices and partisan violence, most strongly by correcting misperceptions of outpartisans’ views – showing that anti-democratic attitudes, although difficult to move, are not intractable. Furthermore, both factor analysis and patterns of intervention effect sizes provide convergent evidence for limited overlap between these sets of outcomes, suggesting that, contrary to popular belief, different strategies are most effective for reducing partisan animosity versus anti-democratic attitudes. Taken together, our findings provide a toolkit of promising strategies for practitioners and shed new theoretical light on challenges facing American democracy.

The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behavior change. To help scholars better understand the social and moral psychology behind public health behavior, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of individual differences and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables.

The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables.

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.