Béatrice Mazoyer

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Research Engineer in Digital Methods


Current Work

I work at the French medialab, an interdisciplinary research laboratory that investigates the role of digital technology in our societies. My research focuses on the collection and analysis of social media data, using natural language processing and data mining methods.


PhD

During my PhD, I worked on mutual influences between social media and traditional news media. My research project was bi-disciplinary: to make sense of datasets containing millions of messages a day, I used machine learning techniques. On the other hand, I used econometrical methods to understand the causal effect of social media activity on publications by news media. My thesis was funded by the Institut National de l’Audiovisuel (the French Multimedia Institute) and co-supervised by CentraleSupélec.

Main supervisor: Céline Hudelot CentraleSupelec, Mathematics and Interaction with Computer Sciences (MICS) Laboratory

Co-supervisor: Nicolas Hervé Institut National de l’Audiovisuel, Research Department


Research Interests

Computer Sciences: Natural Language Processing, Indexing, Information Retrieval, Representation Learning

Economics: Media Economics, Political Economics, Econometrics


Publications

Mazoyer, B., Cagé, J., Hervé, N. & Hudelot, C. (2020). “A French Corpus for Event Detection on Twitter”. In “International Conference on Language Resources and Evaluation (LREC 2020)”, 6220–6227

Evrard, M., Uro, R., Hervé, N. & Mazoyer, B. (2020). “French Tweet Corpus for Automatic Stance Detection”. In “International Conference on Language Resources and Evaluation (LREC 2020)”, 6317–6322

Mazoyer, B., Hervé, N., Hudelot, C., & Cagé, J. (2020). “Représentations lexicales pour la détection non supervisée d’événements dans un flux de tweets : étude sur des corpus français et anglais”. In “Extraction et Gestion des Connaissances (EGC 2020)”

Mazoyer, B., Cagé, J., Hudelot, C., & Viaud, M.-L. (2018). “Real-Time Collection of Reliable and Representative Tweets Datasets Related to News Events”. In “Proceedings of the First International Workshop on Analysis of Broad Dynamic Topics over Social Media (BroDyn 2018) co-located with the 40th European Conference on Information Retrieval (ECIR 2018)”, 23–34

Mazoyer, B., Turenne, N., & Viaud, M.-L. (2017). “Étude des influences réciproques entre médias sociaux et médias traditionnels”. In “Amsaleg, L., Claveau, V. & Tannier, X. Actes de l’atelier Journalisme Computationnel 2017”, 37–40


Communications and Posters

“Automatically detect and archive media events on Twitter” Médialab Research Seminar, December 2019, Sciences Po Paris, France.

Mazoyer, B., Hervé, N., Hudelot, C., & Cagé, J. (2019). “Réduire les biais dans la collecte de tweets”. In “Journée DAHLIA - Informatique et Humanités numériques : quelles problématiques pour quels domaines ?”, June 24, 2019, Nantes, France.

Mazoyer, B., (2019). “Using Text and Image for Topic Detection on Twitter”. Poster at the Workshop on Representation Learning for Complex Data, May 24, 2019, Lyon, France.

“Capter les tweets liés à l’actualité” PEPS EXIA Seminar, October 2016, Marne-la-Vallée, France