| 1. |
- Azevedo, Flavio, et al.
(författare)
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Social and moral psychology of COVID-19 across 69 countries
- 2023
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Ingår i: Scientific Data. - : NATURE PORTFOLIO. - 2052-4463. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 2. |
- Grossmann, Igor, et al.
(författare)
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Insights into the accuracy of social scientists' forecasts of societal change
- 2023
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Ingår i: Nature Human Behaviour. - : Springer Nature. - 2397-3374. ; 7, s. 484-501
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Tidskriftsartikel (refereegranskat)abstract
- How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing the accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists' forecasts were on average no more accurate than those of simple statistical models (historical means, random walks or linear regressions) or the aggregate forecasts of a sample from the general public (N = 802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models and based predictions on prior data. How accurate are social scientists in predicting societal change, and what processes underlie their predictions? Grossmann et al. report the findings of two forecasting tournaments. Social scientists' forecasts were on average no more accurate than those of simple statistical models.
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| 3. |
- Pavlović, Tomislav, et al.
(författare)
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Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning
- 2022
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Ingår i: PNAS Nexus. - : Oxford University Press (OUP). - 2752-6542 .- 2752-6542. ; 1:3
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- 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 multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 ( = 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 results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible 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.
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| 4. |
- Sainudiin, Raazesh, et al.
(författare)
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Characterizing the Twitter network of prominent politicians and SPLC-defined hate groups in the 2016 US presidential election
- 2019
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Ingår i: Social Network Analysis and Mining. - : SPRINGER WIEN. - 1869-5450 .- 1869-5469. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- We characterize the Twitter networks of the major presidential candidates, Donald J. Trump and Hillary R. Clinton, with various American hate groups defined by the US Southern Poverty Law Center (SPLC). We further examined the Twitter networks for Bernie Sanders, Ted Cruz, and Paul Ryan, for 9 weeks around the 2016 election (4 weeks prior to the election and 4 weeks post-election). We carefully account for the observed heterogeneity in the Twitter activity levels across individuals through the null hypothesis of apathetic retweeting that is formalized as a random network model based on the directed, multi-edged, self-looped, configuration model. Our data revealed via a generalized Fisher's exact test that there were significantly many Twitter accounts linked to SPLC-defined hate groups belonging to seven ideologies (Anti-Government, Anti-Immigrant, Anti-LGBT, Anti-Muslim, Alt-Right, White-Nationalist and Neo-Nazi) and also to @realDonaldTrump relative to the accounts of the other four politicians. The exact hypothesis test uses Apache Spark's distributed sort and join algorithms to produce independent samples in a fully scalable way from the null model. Additionally, by exploring the empirical Twitter network we found that significantly more individuals had the fewest retweet degrees of separation simultaneously from Trump and each one of these seven hateful ideologies relative to the other four politicians. We conduct this exploration via a geometric model of the observed retweet network, distributed vertex programs in Spark's GraphX library and a visual summary through neighbor-joined population retweet ideological trees. Remarkably, less than 5% of individuals had three or fewer retweet degrees of separation simultaneously from Trump and one of several hateful ideologies relative to the other four politicians. Taken together, these findings suggest that Trump may have indeed possessed unique appeal to individuals drawn to hateful ideologies; however, such individuals constituted a small fraction of the sampled population.
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| 5. |
- Sainudiin, Raazesh, et al.
(författare)
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Rejecting the Null Hypothesis of Apathetic Retweeting of US Politicians and SPLC-defined Hate Groups in the 2016 US Presidential Election
- 2018
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Ingår i: 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). - : IEEE. - 9781538660515 ; , s. 250-253
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Konferensbidrag (refereegranskat)abstract
- We characterize the Twitter networks of both major presidential candidates, Donald Trump and Hillary Clinton, with various American hate groups defined by the US Southern Poverty Law Center (SPLC). We further examined the Twitter networks for Bernie Sanders, Ted Cruz, and Paul Ryan, for 9 weeks around the 2016 election (4 weeks prior to the election and 4 weeks post-election). By carefully accounting for the observed heterogeneity in the Twitter activity levels across individuals under the null hypothesis of apathetic retweeting that is formalized as a random network model based on the directed, multi-edged, self-looped, configuration model, our data revealed via a generalized Fisher's exact test that there were significantly many Twitter accounts linked to SPLC-defined hate groups belonging to seven ideologies (Anti-Government, Anti-Immigrant, Anti-LGBT, Anti-Muslim, Alt-Right, Neo-Nazi, and White-Nationalist) and also to @realDonaldTrump relative to the accounts of the other four politicians. The exact hypothesis test uses Apache Spark's distributed sort and join algorithms to produce independent samples in a fully scalable way from the null model.
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| 6. |
- Sibley, Chris G., et al.
(författare)
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Profiling authoritarian leaders and followers
- 2019
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Ingår i: TPM - Testing, Psychometrics, Methodology in Applied Psychology. - : CENTRO INFORMAZIONE SCIENTIFICA ECONOMICA SOCIALE-CISES SRL. - 1972-6325. ; 26:3, s. 401-417
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Tidskriftsartikel (refereegranskat)abstract
- Research has long suggested that there may be distinct subpopulations of authoritarian leaders and followers within the broader population. We describe a latent profile analysis of right-wing authoritarianism (RWA) and social dominance orientation (SDO) in a New Zealand national probability sample (N = 18,248) that - for the first time - reliably identifies these two types. Consistent with the positive correlation between SDO and RWA, most people in New Zealand (about 91.2%) expressed comparable levels of RWA and SDO (i.e., moderate-moderate or low-low, but no high-high profile). Two small and distinct subpopulations diverted from this pattern, instead fitting a high-SDO/low-RWA authoritarian leader (1.2%) or low-SDO/high-RWA authoritarian follower (7.6%) profile. Authoritarian leaders tended to show the least concern for human rights, and were least willing to make personal sacrifices for the environment, but tended to support same-sex marriage, while authoritarian followers were particularly opposed to same-sex marriage, and yet highly supportive of human rights. These two profiles represent distinct subpopulations of people within society who are predisposed to seek dominance over others and those predisposed to unquestioningly follow them.
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| 7. |
- Van Bavel, Jay J., et al.
(författare)
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National identity predicts public health support during a global pandemic
- 2022
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Ingår i: Nature Communications. - : Nature Portfolio. - 2041-1723. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Understanding collective behaviour is an important aspect of managing the pandemic response. Here the authors show in a large global study that participants that reported identifying more strongly with their nation reported greater engagement in public health behaviours and support for public health policies in the context of the pandemic. 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.
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