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publications
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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talks
teaching
Artificial Intelligence
Undergraduate course, Institute for Digital Science, Management and Cognition, 2022
This course offers a broad introduction to core concepts in artificial intelligence, including search algorithms, optimization, and basic problem-solving techniques. Through hands-on examples, students explore how AI can be used to model intelligent behavior and automate decision-making.
Web technologies
Undergraduate course, Institute for Digital Science, Management and Cognition, 2022
This course provides a hands-on introduction to the fundamentals of web development. Students learn the basics of HTML, CSS, and JavaScript to build simple, interactive websites, while gaining an understanding of how the web works and best practices in code structure.
Web Complement
Undergraduate course, Charlemagne University Institute of Technology, 2023
This course builds on basic web development skills to deepen understanding of modern front-end and back-end technologies. Students learn to structure dynamic web applications using HTML, CSS, JavaScript, and frameworks such as React and Node.js, with a focus on clean design, API integration, and responsive development practices.
Data Visualization
Graduate course, TELECOM Nancy Engineering School, 2024
This course introduces the fundamentals of data visualization using Python and popular libraries such as Matplotlib, Seaborn, and Plotly. Students learn to explore, analyze, and effectively communicate data through clear and insightful visualizations, with an emphasis on best practices in visual design.