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A new way to characterize learning datasets.
Published in 14th International Conference on Computer Supported Education, 2022
Recommended citation: Treuillier, C., & Boyer, A. (2022, April). A new way to characterize learning datasets. In 14th International Conference on Computer Supported Education (pp. 35-44). SCITEPRESS-Science and Technology Publications.
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Don’t burst blindly: for a better use of natural language processing to fight opinion bubbles in news recommendations
Published in First Workshop on Natural Language Processing for Political Science, 2022
Recommended citation: Dufraisse, E., Treuillier, C., Brun, A., Tourille, J., Castagnos, S., & Popescu, A. (2022, June). Dont burst blindly: for a better use of natural language processing to fight opinion bubbles in news recommendations. In First Workshop on Natural Language Processing for Political Science (pp. 79-85).
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Being diverse is not enough: Rethinking diversity evaluation to meet challenges of news recommender systems
Published in FairUMAP workshop as part of the 30st ACM Conference on User Modeling, Adaptation and Personalization, 2022
Recommended citation: Treuillier, C., Castagnos, S., Dufraisse, E., & Brun, A. (2022, July). Being diverse is not enough: Rethinking diversity evaluation to meet challenges of news recommender systems. In Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (pp. 222-233).
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Learning profiles to assess educational prediction systems.
Published in International Conference on Artificial Intelligence in Education, 2022
Recommended citation: Ben Soussia, A., Treuillier, C., Roussanaly, A., & Boyer, A. (2022, July). Learning profiles to assess educational prediction systems. In International Conference on Artificial Intelligence in Education (pp. 41-52). Cham: Springer International Publishing.
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A multi-factorial analysis of polarization on social media
Published in 31st ACM Conference on User Modeling, Adaptation and Personalization, 2023
Recommended citation: Treuillier, C., Brun, A., & Castagnos, S. (2023, June). A multi-factorial analysis of polarization on social media. In Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (pp. 1-6).
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Gaining a Better Understanding of Online Polarization by Approaching it as a Dynamic Process
Published in Scientific Reports, 2024
Recommended citation: Treuillier, C., Castagnos, S., Lagier, C. et al. Gaining a better understanding of online polarization by approaching it as a dynamic process. Sci Rep 14, 8702 (2024). https://doi.org/10.1038/s41598-024-58915-w
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All Polarized but Still Different: a Multi-factorial Metric to Discriminate between Polarization Behaviors on Social Media
Published in 39th ACM/SIGAPP Symposium on Applied Computing , 2024
Recommended citation: Treuillier, C., Castagnos, S., & Brun, A. (2024, April). All Polarized but Still Different: a Multi-factorial Metric to Discriminate between Polarization Behaviors on Social Media. In Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing (pp. 1469-1478).
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Beyond Trade-offs: Unveiling Fairness-Constrained Diversity in News Recommender Systems.
Published in 32nd ACM Conference on User Modeling, Adaptation and Personalization , 2024
Recommended citation: Treuillier, C., Castagnos, S., Özgöbek, Ö., & Brun, A. (2024, June). Beyond Trade-offs: Unveiling Fairness-Constrained Diversity in News Recommender Systems. In Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (pp. 143-148).
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