Ziv Epstein

3.2k total citations · 3 hit papers
24 papers, 1.6k citations indexed

About

Ziv Epstein is a scholar working on Sociology and Political Science, Artificial Intelligence and Safety Research. According to data from OpenAlex, Ziv Epstein has authored 24 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Sociology and Political Science, 8 papers in Artificial Intelligence and 7 papers in Safety Research. Recurrent topics in Ziv Epstein's work include Misinformation and Its Impacts (11 papers), Social Media and Politics (5 papers) and Ethics and Social Impacts of AI (5 papers). Ziv Epstein is often cited by papers focused on Misinformation and Its Impacts (11 papers), Social Media and Politics (5 papers) and Ethics and Social Impacts of AI (5 papers). Ziv Epstein collaborates with scholars based in United States, Canada and Mexico. Ziv Epstein's co-authors include David G. Rand, Gordon Pennycook, Antonio A. Arechar, Dean Eckles, Mohsen Mosleh, Matthew Groh, Chaz Firestone, Rosalind W. Picard, Hope Schroeder and Laura Herman and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Ziv Epstein

23 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Shifting attention to accuracy can reduce misinformation online

2021 556 citations Gordon Pennycook, Ziv Epstein et al. Nature profile →
Art and the science of generative AI

2023 314 citations Ziv Epstein, Matthew Groh et al. profile →
Understanding and combatting misinformation across 16 countries on six continents

2023 79 citations Antonio A. Arechar, Jennifer Allen et al. Nature Human Behaviour profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ziv Epstein United States	15	928	469	344	242	187	24	1.6k
Yubo Kou United States	24	1.0k 1.1×	433 0.9×	362 1.1×	70 0.3×	127 0.7×	73	1.9k
Motahhare Eslami United States	18	808 0.9×	474 1.0×	291 0.8×	115 0.5×	609 3.3×	52	1.7k
Andrew McStay United Kingdom	13	602 0.6×	262 0.6×	288 0.8×	109 0.5×	180 1.0×	42	1.1k
Asimina Vasalou United Kingdom	19	584 0.6×	195 0.4×	136 0.4×	167 0.7×	61 0.3×	83	1.6k
Wai‐Tat Fu United States	23	426 0.5×	494 1.1×	206 0.6×	185 0.8×	45 0.2×	105	1.8k
Autumn Edwards United States	23	761 0.8×	859 1.8×	299 0.9×	178 0.7×	229 1.2×	76	2.0k
Kristen Vaccaro United States	13	503 0.5×	345 0.7×	205 0.6×	78 0.3×	373 2.0×	19	1.1k
Ellen R. Tauber United States	6	732 0.8×	806 1.7×	205 0.6×	198 0.8×	209 1.1×	8	2.1k
Frank Bentley United States	21	589 0.6×	416 0.9×	124 0.4×	82 0.3×	41 0.2×	73	1.8k
Stephann Makri United Kingdom	22	381 0.4×	197 0.4×	256 0.7×	100 0.4×	61 0.3×	73	1.5k

Countries citing papers authored by Ziv Epstein

Since Specialization

Citations

This map shows the geographic impact of Ziv Epstein'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 Ziv Epstein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ziv Epstein more than expected).

Fields of papers citing papers by Ziv Epstein

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ziv Epstein. 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 Ziv Epstein. The network helps show where Ziv Epstein may publish in the future.

Co-authorship network of co-authors of Ziv Epstein

This figure shows the co-authorship network connecting the top 25 collaborators of Ziv Epstein. A scholar is included among the top collaborators of Ziv Epstein 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 Ziv Epstein. Ziv Epstein is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wittenberg, Chloe, et al.. (2025). Labeling AI-generated media online. PNAS Nexus. 4(6). pgaf170–pgaf170. 3 indexed citations

Danry, Valdemar, Pat Pataranutaporn, Matthew Groh, & Ziv Epstein. (2025). Deceptive Explanations by Large Language Models Lead People to Change their Beliefs About Misinformation More Often than Honest Explanations. 1–31. 2 indexed citations

Wittenberg, Chloe, Ziv Epstein, Adam J. Berinsky, & David G. Rand. (2024). Labeling AI-Generated Content: Promises, Perils, and Future Directions. 9 indexed citations

Schroeder, Hope, Ziv Epstein, Simon T. Perrault, et al.. (2024). LLMs as Research Tools: Applications and Evaluations in HCI Data Work. IT University Of Copenhagen (IT University of Copenhagen). 1–7. 17 indexed citations

Ugander, Johan & Ziv Epstein. (2024). The Art of Randomness: Sampling and Chance in the Age of Algorithmic Reproduction. SHILAP Revista de lepidopterología. 6(4). 1 indexed citations

Arechar, Antonio A., Jennifer Allen, Adam J. Berinsky, et al.. (2023). Understanding and combatting misinformation across 16 countries on six continents. Nature Human Behaviour. 7(9). 1502–1513. 79 indexed citations breakdown →

Epstein, Ziv, et al.. (2022). Do Explanations Increase the Effectiveness of AI-Crowd Generated Fake News Warnings?. Proceedings of the International AAAI Conference on Web and Social Media. 16. 183–193. 30 indexed citations

Pennycook, Gordon, Ziv Epstein, Mohsen Mosleh, et al.. (2021). Shifting attention to accuracy can reduce misinformation online. Nature. 592(7855). 590–595. 556 indexed citations breakdown →

Epstein, Ziv, et al.. (2021). Digital literacy is associated with more discerning accuracy judgments but not sharing intentions. SHILAP Revista de lepidopterología. 40 indexed citations

10.

Groh, Matthew, Ziv Epstein, Chaz Firestone, & Rosalind W. Picard. (2021). Deepfake detection by human crowds, machines, and machine-informed crowds. Proceedings of the National Academy of Sciences. 119(1). 122 indexed citations

11.

Groh, Matthew, Ziv Epstein, Rosalind W. Picard, & Chaz Firestone. (2021). Human Detection of Deepfakes: A Role for Holistic Face Processing. Journal of Vision. 21(9). 2390–2390. 2 indexed citations

12.

Epstein, Ziv, et al.. (2021). Developing an accuracy-prompt toolkit to reduce COVID-19 misinformation online. SHILAP Revista de lepidopterología. 35 indexed citations

13.

Pennycook, Gordon, Ziv Epstein, Mohsen Mosleh, et al.. (2020). Understanding and Reducing the Spread of Misinformation Online. ACR North American Advances. 27 indexed citations

14.

Epstein, Ziv, Sydney Levine, David G. Rand, & Iyad Rahwan. (2020). Who Gets Credit for AI-Generated Art?. iScience. 23(9). 101515–101515. 81 indexed citations

15.

Epstein, Ziv, Gordon Pennycook, & David G. Rand. (2020). Will the Crowd Game the Algorithm?. 1–11. 47 indexed citations

16.

Epstein, Ziv, Alexander Peysakhovich, & David G. Rand. (2016). The Good, the Bad, and the Unflinchingly Selfish: Cooperative Decision-Making Can Be Predicted with High Accuracy Using Only Three Behavioral Types. SSRN Electronic Journal. 7 indexed citations

17.

Epstein, Ziv, Alexander Peysakhovich, & David G. Rand. (2016). The Good, the Bad, and the Unflinchingly Selfish. 70. 547–559. 14 indexed citations

18.

Epstein, Ziv, et al.. (2015). Using Machine Learning To Populate A Markov Model By Mining Big Data Directly From Hospital Ehrs – An Application To Dynamically Predict Hospital-Acquired Pressure Ulcers. Value in Health. 18(7). A694–A694.

19.

Rand, David G. & Ziv Epstein. (2014). Risking Your Life without a Second Thought: Intuitive Decision-Making and Extreme Altruism. PLoS ONE. 9(10). e109687–e109687. 97 indexed citations

20.

Rand, David G. & Ziv Epstein. (2014). Risking Your Life Without a Second Thought: Intuitive Decision-Making and Extreme Altruism. SSRN Electronic Journal. 4 indexed citations

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.

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