Berkeley J. Dietvorst
- Safety Research top 0.2%
- Artificial Intelligence top 1%
- Sociology and Political Science top 2%
- Cognitive Neuroscience top 5%
- Social Psychology top 5%
- Co-authors
- Cade MasseyJoseph P. SimmonsDaniel M. BartelsUri SimonsohnMaurice E. SchweitzerHengchen DaiKatherine L. MilkmanOleg Urminsky
- Topics
- Decision-Making and Behavioral Economics (11 papers)Forecasting Techniques and Applications (7 papers)Behavioral Health and Interventions (5 papers)
- Partner nations
- United StatesSpain
In The Last Decade
Berkeley J. Dietvorst
18 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 120
- Safety Research 1.1k
- Artificial Intelligence 848
- Sociology and Political Science 551
- Cognitive Neuroscience 407
- Social Psychology 372
Countries citing papers authored by Berkeley J. Dietvorst
This map shows the geographic impact of Berkeley J. Dietvorst'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 Berkeley J. Dietvorst with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Berkeley J. Dietvorst more than expected).
Fields of papers citing papers by Berkeley J. Dietvorst
This network shows the impact of papers produced by Berkeley J. Dietvorst. 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 Berkeley J. Dietvorst. The network helps show where Berkeley J. Dietvorst may publish in the future.
Co-authorship network of co-authors of Berkeley J. Dietvorst
This figure shows the co-authorship network connecting the top 25 collaborators of Berkeley J. Dietvorst. A scholar is included among the top collaborators of Berkeley J. Dietvorst based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Berkeley J. Dietvorst. Berkeley J. Dietvorst is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 5 | |
| 3 | 0 | |
| 4 | 26 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 52 | |
| 8 | 0 | |
| 9 | 4 | |
| 10 | 153 | |
| 11 | 6 | |
| 12 | 12 | |
| 13 | 12 | |
| 14 | Overcoming Algorithm Aversion | 1 |
| 15 | 4 | |
| 16 | Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Thembreakdown → | 676 |
| 17 | 9 | |
| 18 | Algorithm aversion: People erroneously avoid algorithms after seeing them err.breakdown → | 1386 |
| 19 | 19 | |
| 20 | 131 |
About Berkeley J. Dietvorst
Berkeley J. Dietvorst is a scholar working on General Decision Sciences, Applied Psychology and Management Science and Operations Research, having authored 21 papers that have together received 2.5k indexed citations. Recurring topics across this work include Decision-Making and Behavioral Economics (11 papers), Forecasting Techniques and Applications (7 papers) and Behavioral Health and Interventions (5 papers). The work is most often cited by research in Health Informatics (259 citations), General Decision Sciences (259 citations) and Safety Research (1.1k citations). Berkeley J. Dietvorst has collaborated with scholars based in United States and Spain. Frequent co-authors include Cade Massey, Joseph P. Simmons, Daniel M. Bartels, Uri Simonsohn, Maurice E. Schweitzer, Hengchen Dai, Katherine L. Milkman, Oleg Urminsky, Christian Hildebrand and Julian De Freitas. Their work appears in journals such as Academy of Management Journal, Management Science and Journal of Consumer Research.
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.