David G. Rand
Impact in
- Safety Research top 0.01%
- Experimental Behavioral Economics Studies
- General Decision Sciences top 0.2%
Papers in
-
- Evolutionary Game Theory and Cooperation 124
- Misinformation and Its Impacts 91
- Social and Intergroup Psychology 32
- Safety Research 134
- Experimental Behavioral Economics Studies 131
- Co-authors
- Gordon Pennycook (66 shared papers)Martin A. Nowak (37 shared papers)Jillian Jordan (22 shared papers)Joshua D. Greene (7 shared papers)Nicholas A. Christakis (9 shared papers)Alexander Peysakhovich (12 shared papers)Tyrone D. Cannon (5 shared papers)Adam Bear (11 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (25 papers)Nature (11 papers)PLoS ONE (10 papers)Nature Communications (10 papers)Judgment and Decision Making (10 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
David G. Rand
302 papers receiving 25.5k citations
David G. Rand's Hit Papers
Peers
Comparison fields: 5 of 200
- Safety Research 6.7k
- General Decision Sciences 1.2k
- Communication 4.1k
- Sociology and Political Science 18.5k
- Cognitive Neuroscience 4.3k
Countries citing papers authored by David G. Rand
This map shows the geographic impact of David G. Rand's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David G. Rand with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David G. Rand more than expected).
Fields of papers citing papers by David G. Rand
This network shows the impact of papers produced by David G. Rand. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David G. Rand. The network helps show where David G. Rand may publish in the future.
Co-authors
The 25 scholars most cited alongside David G. Rand, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 308 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Structural Topic Models for Open‐Ended Survey Responses Hit paper breakdown → | 2014 | 1258 |
| 2 | Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning Hit paper breakdown → | 2018 | 1190 |
| 3 | Statistical physics of human cooperation Hit paper breakdown → | 2017 | 1168 |
| 4 | Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention Hit paper breakdown → | 2020 | 1119 |
| 5 | Human cooperation Hit paper breakdown → | 2013 | 942 |
| 6 | Spontaneous giving and calculated greed Hit paper breakdown → | 2012 | 885 |
| 7 | Prior exposure increases perceived accuracy of fake news. Hit paper breakdown → | 2018 | 714 |
| 8 | The Psychology of Fake News Hit paper breakdown → | 2021 | 678 |
| 9 | Shifting attention to accuracy can reduce misinformation online Hit paper breakdown → | 2021 | 603 |
| 10 | Winners don’t punish Hit paper breakdown → | 2008 | 536 |
| 11 | Social heuristics shape intuitive cooperation Hit paper breakdown → | 2014 | 536 |
| 12 | Fighting misinformation on social media using crowdsourced judgments of news source quality Hit paper breakdown → | 2019 | 526 |
| 13 | Positive Interactions Promote Public Cooperation Hit paper breakdown → | 2009 | 521 |
| 14 | The promise of Mechanical Turk: How online labor markets can help theorists run behavioral experiments Hit paper breakdown → | 2011 | 513 |
| 15 | Political sectarianism in America Hit paper breakdown → | 2020 | 497 |
| 16 | Who falls for fake news? The roles of bullshit receptivity, overclaiming, familiarity, and analytic thinking Hit paper breakdown → | 2019 | 479 |
| 17 | Dynamic social networks promote cooperation in experiments with humans Hit paper breakdown → | 2011 | 476 |
| 18 | The Implied Truth Effect: Attaching Warnings to a Subset of Fake News Headlines Increases Perceived Accuracy of Headlines Without Warnings Hit paper breakdown → | 2020 | 400 |
| 19 | Divine intuition: Cognitive style influences belief in God. Hit paper breakdown → | 2011 | 385 |
| 20 | Third-party punishment as a costly signal of trustworthiness Hit paper breakdown → | 2016 | 310 |
About David G. Rand
David G. Rand is a scholar working on Sociology and Political Science, Safety Research, Cognitive Neuroscience, Communication and Experimental and Cognitive Psychology, having authored 308 papers that have together received 26.4k indexed citations. Recurring topics across this work include Experimental Behavioral Economics Studies (131 papers), Evolutionary Game Theory and Cooperation (124 papers), Misinformation and Its Impacts (91 papers), Psychology of Moral and Emotional Judgment (60 papers), Social Media and Politics (45 papers), Evolutionary Psychology and Human Behavior (41 papers), Social and Intergroup Psychology (32 papers) and Opinion Dynamics and Social Influence (30 papers). The work is most often cited by research in Safety Research (6.7k citations), General Decision Sciences (1.2k citations), Communication (4.1k citations), Sociology and Political Science (18.5k citations) and Cognitive Neuroscience (4.3k citations). David G. Rand has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Gordon Pennycook, Martin A. Nowak, Jillian Jordan, Joshua D. Greene, Nicholas A. Christakis, Alexander Peysakhovich, Tyrone D. Cannon, Adam Bear, Anna Dreber and Jonathon McPhetres. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature, PLoS ONE, Nature Communications and Judgment and Decision Making.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.