Zeitschriftenartikel (27)
2024
Zeitschriftenartikel
Bersch, C., , , , Dong, M., , , , , Soraperra, I., , , , & Köbis, N. (2024). Risks and protective measures for synthetic relationships. Nature Human Behaviour, 8, 1834–1836. https://doi.org/10.1038/s41562-024-02005-4
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Werner, T. (2024). A new sociology of humans and machines. Nature Human Behaviour, 8, 1864–1876. https://doi.org/10.1038/s41562-024-02001-8
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von Schenk, A., Klockmann, V., , Rahwan, I., & Köbis, N. (2024). Lie detection algorithms disrupt the social dynamics of accusation behavior. iScience, 27(7), Article 110201. https://doi.org/10.1016/j.isci.2024.110201
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Soraperra, I., , & (2024). Giving (in) to help an identified person. Journal of Experimental Social Psychology, 110, Article 104557. https://doi.org/10.1016/j.jesp.2023.104557
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Bermudez Schettino, R., , , , , & (2024). An interpretable data‑driven prediction model to anticipate scoliosis in spinal muscular atrophy in the era of (gene‑) therapies. Scientific Reports, 14, Article 11838. https://doi.org/10.1038/s41598-024-62720-w
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Yakura, H. (2024). Evaluating large language models’ ability using a psychiatric screening tool based on metaphor and sarcasm scenarios. Journal of Intelligence, 12(7), Article 70. https://doi.org/10.3390/jintelligence12070070
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Nussberger, A.-M. (2024). Gratitude is morally sensitive. Personality and Social Psychology Bulletin, 50(3), 406–422. https://doi.org/10.1177/01461672221092273
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2024
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Köbis, N. (2024). Artificial intelligence (AI) (and anti-corruption). In & (Eds.), Elgar encyclopedia of corruption and society (pp. 17–22). Edward Elgar.
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Dong, M. (2024). False moral superiority and heroism. In , , & (Eds.), Encyclopedia of heroism studies (pp. 585–588). Springer. https://doi.org/10.1007/978-3-031-48129-1_243
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Köbis, N., & (2024). Artificial intelligence as a weapon to fight corruption: Civil society actors on the benefits and risks of existing bottom-up approaches. In (Ed.), Digital media and grassroots anti-corruption: Contexts, platforms and data of anti-corruption technologies worldwide (pp. 229–249). Edward Elgar Publishing. https://doi.org/10.4337/9781802202106.00020
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2024
Konferenzbeitrag
Yakura, H. (2024). Coaching copilot: Blended form of an LLM-powered chatbot and a human coach to effectively support self-reflection for leadership growth. In & (Eds.), CUI '24: Proceedings of the 6th ACM Conference on Conversational User Interfaces. ACM Digital Library. https://doi.org/10.1145/3640794.3665549
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Yakura, H., & (2024). PrISM-Observer: Intervention agent to help users perform everyday procedures sensed using a smartwatch. In , , , & (Eds.), UIST '24: Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology. ACM Digital Library. https://doi.org/10.1145/3654777.3676350
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Baumann, F., , , Rahwan, I., , & (2024). Optimal engagement-diversity tradeoffs in social media. In WWW '24: Proceedings of the ACM on Web Conference 2024 (pp. 288–299). https://doi.org/10.1145/3589334.3645713
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Engelmann, N., , , & (2024). Understanding rule enforcement using drift diffusion models. In , , , , & (Eds.), Proceedings of the Annual Meeting of the Cognitive Science Society (Vol. 46, pp. 114–120). UC Merced.
Forschungspapier (2)
2024
Forschungspapier
Werner, T. (2024). What drives demand for loot boxes? An experimental study (Discussion Paper / DFG Research Unit: "Consumer Preferences, Consumer Mistakes, and Firms' Response" (FOR 5392) No. 2024/05). Heinrich-Heine-University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE), DFG Research Unit: "Consumer Preferences, Consumer Mistakes, and Firms' Response" (FOR 5392).
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Werner, T. (2024). Human-machine interactions in pricing: Evidence from two large-scale field experiments (DICE Discussion Paper No. 412). Heinrich-Heine-University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
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2024
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Awad, E., , Rahwan, I., & Rahwan, Z. (2024). Heterogeneity in charitable giving preferences from over 2 million decisions worldwide. OSF Preprints, September 11, 2024. https://doi.org/10.31219/osf.io/28g3z
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Klockmann, V., & von Schenk, A. (2024). Human and algorithmic cooperation: Parameters matter! (Version posted online November 28, 2024). SSRN eLibrary, October 21, 2024. https://doi.org/10.2139/ssrn.4955708
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Dong, M., , & Rahwan, I. (2024). False consensus biases AI against vulnerable stakeholders. SSRN eLibrary, June 28, 2024. https://doi.org/10.2139/ssrn.4876227
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Gupta, P., & (2024). Machine learning and optimization-based approaches to duality in statistical physics. arXiv, 2411.04838. https://doi.org/10.48550/arXiv.2411.04838
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