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Articles by Mohammad Atari
Saturation of moral language predicts lower content engagement on social media
Abstract Moral language often travels widely online, but does more moral content always correspond to higher engagement? We analysed 1,621,147 observations across 13 socio-political topics on Twitter (n = 530,104), Reddit (n = 1,048,653) and 8chan (n = 42,390).
Metamorality: When Moral Compasses Lead to Moral Impasses
Conflicts of Interest The authors declare no conflicts of interest. Data Availability Statement The authors have nothing to report. References 2019. “Social Cognition 2.0: An Interactive Memory Systems Account.” Trends in Cognitive Sciences 23, no. 1: 21–33. https://doi.org/10.1016/j.tics.2018.10.002. , , and . 2020. “Foundations of Morality in Iran.” Evolution and Human Behavior 41, no. 5: 367–384. https://doi.org/10.1016/j.evolhumbehav.2020.07.014. , , , , , and . 2023.
A reporting checklist for large language models in behavioural science
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Large language models offer new opportunities for behavioural science, but their rapid evolution poses challenges for research rigour. We introduce a consensus-based reporting checklist to improve transparency, reproducibility and ethical accountability of large-language-model-based research in the behavioural sciences. You have full access to this article via your institution.
By Stefan Feuerriegel, Christopher Barrie, M. J. Crockett, Laura K. Globig, Killian McLoughlin, Dan-Mircea Mirea, Arthur Spirling, Diyi Yang, Tim Althoff, Maria Antoniak, Lisa P. Argyle, Ashwini Ashokkumar, Mohammad Atari, Hannah Bailey, Kevin Bauer, Umang Bhatt, Yidong Chai, Tanmoy Chakraborty Verified, Yanto Chandra, Huimin Chen, Hal Daumé III, Gianmarco De Francisci Morales, Morteza Dehghani, Danica Dillion, Johannes C. Eichstaedt, Kerstin Förster, Dominique Geissler, Kurt Gray, Thomas L. Griffiths, Hartmann Jochen, Oliver Hauser, James He, Rahul Hemrajani, Felix Holzmeister, Angel Hsing-Chi Hwang, Tiancheng Hu, Anna Ivanova, Nils Köbis, Yara Kyrychenko, Himabindu Lakkaraju, Jia Liu, Abdurahman Maarouf, Sebastian Maier, Lennart Meincke, Rada Mihalcea, Brent Mittelstadt, Saif M. Mohammad, Mor Naaman, Oded Netzer, Alice Oh, Desmond C. Ong, Francesco Pierri, Barbara Plank, Iyad Rahwan, Talal Rahwan, Pooja Rao, Claire Robertson, David Rothschild, Matthew Salganik, Eric Schulz, Chirag Shah, Yash Shrestha, Ekaterina Shutova, Alexandra Siegel, Almog Simchon, Huan Sun, Malte Toetzke, Jay Van Bavel, Michelle Vaccaro, Jennifer Vaughan, Effy Vayena, Pedro O. S. Vaz-de-Melo, Briana Vecchione, Angelina Wang, Robert West, Robb Willer, Dirk U. Wulff, Renwen Zhang, Simone Zhang, Steve Rathje, Manoel Horta Ribeiro
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Nature
Verified
Research: How the “Accent Penalty” Determines Who Gets Heard
by Aliah Zewail, Amir Sepehri, Reihane Boghrati and Mohammad Atari March 17, 2026 HBR Staff/Boston Public Library/Unsplash In modern organizations, leaders tacitly assume that good ideas rise on their merits: The most compelling argument wins, or the clearest insight gains traction. In principle, expertise, evidence, and originality should objectively determine whose ideas garner attention. In practice, however, influence often depends on something far less visible: a speaker’s accent.
The chronospatial revolution in psychology - Nature Human Behaviour
Abstract Psychology’s definition and scope have shifted over the discipline’s short history, yet it has largely remained ahistorical and geographically narrow. Here we call for psychology to become a historical and geographical science, a transformation we term the chronospatial revolution. We list four barriers to this shift in psychology: problems in scope, data, synergy and theory.
Large Language Models based on historical text could offer informative tools for behavioral science
The study of human behavior traditionally focuses on the here and now. After all, people cannot take surveys or participate in experiments if they are not alive today. Here, we propose a way to address this limitation—namely, the use of Historical Large Language Models (HLLMs). These generative models, trained on corpora of historical texts, may provide populations of simulated historical participants.
Investigating the role of group-based morality in extreme behavioral expressions of prejudice - Nature Communications
Abstract Understanding motivations underlying acts of hatred are essential for developing strategies to prevent such extreme behavioral expressions of prejudice (EBEPs) against marginalized groups. In this work, we investigate the motivations underlying EBEPs as a function of moral values. Specifically, we propose EBEPs may often be best understood as morally motivated behaviors grounded in people’s moral values and perceptions of moral violations.
Sex differences in moral judgements across 67 countries
1. Introduction Fundamental moral concerns such as care, fairness, ingroup loyalty, respect for authority, and purity govern human psychology across cultures [1]. A growing programme of research suggests that women and men endorse moral concerns and social preferences to different degrees and that these sex differences vary across cultures [2–5].
Sex differences in moral judgements across 67 countries
Restricted accessResearch articles Abstract Most of the empirical research on sex differences and cultural variations in morality has relied on within-culture analyses or small-scale cross-cultural data. To further broaden the scientific understanding of sex differences in morality, the current research relies on two international samples to provide the first large-scale examination of sex differences in moral judgements nested within cultures.
Body Maps of Moral Concerns
Avramova, Y. R., Inbar, Y. (2013). Emotion and moral judgment. Wiley Interdisciplinary Reviews: Cognitive Science, 4, 169–178. doi:10.1002/wcs.1216 Google Scholar | Crossref | Medline | ISI Barrett, L. F., Quigley, K. S., Bliss-Moreau, E., Aronson, K. R. (2004). Interoceptive sensitivity and self-reports of emotional experience. Journal of Personality and Social Psychology, 87, 684–697. doi:10.1037/0022-3514.87.5.684 Google Scholar | Crossref | Medline | ISI Bowman, S. R., Angeli, G., Potts, C., Manning, C.
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