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N. Tintarev

Key publications
Cau, F., Hauptmann, H., Spano, L. D., & Tintarev, N. (2023). Effects of Logic-Style Explanations and Uncertainty on Users’ Decisions. Paper presented at 28th Annual Conference on Intelligent User Interfaces (IUI)
, Sydney, New South Wales, Australia.
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Wu, Z., Draws, T., Cau, F., Barile, F., Rieger, A., & Tintarev, N. (2023). Explaining Search Result Stances to Opinionated People. In L. Longo (Ed.), Explainable Artificial Intelligence (pp. 573-596). Springer. https://doi.org/10.1007/978-3-031-44067-0_29
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Hada, R., Ebrahimi Fard, A., Shugars, S., Bianchi, F., Rossini, P., Hovy, D., Tromble, R., & Tintarev, N. (2023). Beyond Digital "echo Chambers": The Role of Viewpoint Diversity in Political Discussion. In WSDM 2023 - Proceedings of the 16th ACM International Conference on Web Search and Data Mining (pp. 33-41). Association for Computing Machinery (ACM). https://doi.org/10.1145/3539597.3570487
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Yurrita, M., Draws, T., Balayn, A., Murray-Rust, D., Tintarev, N., & Bozzon, A. (2023). Disentangling Fairness Perceptions in Algorithmic Decision-Making: the Effects of Explanations, Human Oversight, and Contestability. In CHI 2023 - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems Article 134 Association for Computing Machinery. https://doi.org/10.1145/3544548.3581161
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Draws, T., Inel, O., Tintarev, N., Baden, C., & Timmermans, B. (2022). Comprehensive Viewpoint Representations for a Deeper Understanding of User Interactions With Debated Topics. In CHIIR '22: ACM SIGIR Conference on Human Information Interaction and Retrieval (pp. 135-145). Association for Computing Machinery (ACM). https://doi.org/10.1145/3498366.3505812
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Recent publications
  • Najafian, S., Musick, G., Knijnenburg, B., & Tintarev, N. (2024). How do people make decisions in disclosing personal information in tourism group recommendations in competitive versus cooperative conditions? User Modeling and User-Adapted Interaction, 34(3), 549-581. https://doi.org/10.1007/s11257-023-09375-w
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  • Barile, F., Cau, F. M., & Tintarev, N. (2024). A Preliminary Analysis on Self and Peer Evaluation of Personality Models for Recommender Systems. In UMAP 2024 - Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (pp. 70-74). Association for Computing Machinery (ACM). https://doi.org/10.1145/3631700.3664864
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  • Barile, F., Cau, F. M., & Tintarev, N. (2024). A Preliminary Study of the Impact of Personality on Satisfaction in Group Contexts. In UMAP 2024 - Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (pp. 319-328). Association for Computing Machinery (ACM). https://doi.org/10.1145/3631700.3664893
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  • Tintarev, N., Knijnenburg, B. P., & Willemsen, M. C. (2024). Measuring the benefit of increased transparency and control in news recommendation. Ai Magazine, 45(2), 212-226. https://doi.org/10.1002/aaai.12171
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  • Rieger, A., Draws, T., Theune, M., & Tintarev, N. (2024). Nudges to Mitigate Confirmation Bias during Web Search on Debated Topics: Support vs. Manipulation. Acm Transactions on the Web, 18(2), Article 27. https://doi.org/10.1145/3635034
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  • Kruse, J., Michiels, L., Starke, A., Tintarev, N., & Vrijenhoek, S. (2024). NORMalize: A Tutorial on the Normative Design and Evaluation of Information Access Systems. In CHIIR 2024 - Proceedings of the 2024 Conference on Human Information Interaction and Retrieval (pp. 422-424). Association for Computing Machinery (ACM). https://doi.org/10.1145/3627508.3638319
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  • Felfernig, A., Tintarev, N., Trang Tran, T. N., & Stettinger, M. (2024). Explanations for Groups. In Group Recommender Systems: An Introduction (pp. 109-131). Springer. https://doi.org/10.1007/978-3-031-44943-7_6
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  • Cau, F. M., & Tintarev, N. (2024). Navigating the Thin Line: Examining User Behavior in Search to Detect Engagement and Backfire Effects. In N. Goharian, N. Tonellotto, Y. He, A. Lipani, G. McDonald, C. Macdonald, & I. Ounis (Eds.), Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Proceedings (Vol. 14611 LNCS, pp. 403-419). Springer Verlag. https://doi.org/10.1007/978-3-031-56066-8_30
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  • Sivaprasad, A., Reiter, E., Tintarev, N., & Oren, N. (2024). Evaluation of Human-Understandability of Global Model Explanations Using Decision Tree. In S. Nowaczyk, P. Biecek, N. C. Chung, M. Vallati, P. Skruch, J. Jaworek-Korjakowska, S. Parkinson, A. Nikitas, M. Atzmüller, T. Kliegr, U. Schmid, S. Bobek, N. Lavrac, M. Peeters, R. van Dierendonck, S. Robben, E. Mercier-Laurent, G. Kayakutlu, M. L. Owoc, K. Mason, A. Wahid, P. Bruno, F. Calimeri, F. Cauteruccio, G. Terracina, D. Wolter, J. L. Leidner, M. Kohlhase, ... V. Dimitrova (Eds.), Artificial Intelligence. ECAI 2023 International Workshops - XAI^3, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, 2023, Proceedings (Vol. 1947, pp. 43-65). Springer. https://doi.org/10.1007/978-3-031-50396-2_3
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  • Cau, F. M., Hauptmann, H., Spano, L. D., & Tintarev, N. (2023). Effects of AI and Logic-Style Explanations on Users’ Decisions Under Different Levels of Uncertainty. Transactions on Interactive Intelligent Systems, 13(4), Article 22. https://doi.org/10.1145/3588320
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