There is no longer any need to prove that digital technology, the Internet and the web have led to a revolution, particularly in the way people get information. Like any revolution, it is followed by a series of issues : equal treatment of users and suppliers, ecologically sustainable consumption, freedom of expression and censorship, etc. Research needs to provide a clear vision of these stakes.
Among these issues, we can talk about two phenomena : the echo chamber phenomenon and the filter bubble phenomenon. These two phenomena are linked to the lack of diversity of information visible on the Internet, and one may wonder about the impact of recommendation algorithms. Even if this is our primary motivation, we are moving away from this subject to propose a general scientific framework to analyze diversity. We find that the graph formalism is useful enough to be able to represent relational data. More precisely, we will analyze relational data with entities of different natures. This is why we chose the n-part graph formalism because this is a good way to represent a great diversity of data. Even if the first data we studied is related to recommendation algorithms (music consumption or purchase of articles on a platform) we will see over the course of the manuscript how this formalism can be adapted to other types of data (politicized users on Twitter, guests of television shows, establishment of NGOs in different States ...). There are several objectives in this study :
- Mathematically define diversity indicators on the n-part graphs.
- Algorithmically define how to calculate them.
- Program these algorithms to make them a usable computer object.
- Use these programs on quite varied data.
- See the different meanings that our indicators can have.
Defence : 12/04/2020 - 11h - Zoom - https://us02web.zoom.us/j/82011212125?pwd=KzBpZi9DZy9SNHZYYmNuc3VkTTZUUT09
Jury members :
Mme ROBARDET Céline (Professeure au LIRIS), [Rapporteure]
M ABDESSALEM Talel (Professeur à l'INFRES), [Rapporteur]
Mme LUENGO Vanda (Professeure au Lip6), Examinatrice
M CAZABET Rémy (Maître de conférence au LIRIS)
M HERVE Nicolas (Chercheur à l'INA)
M. BENBOUZID Bilel (Maître de conférence au LISIS)
Mme MAGNIEN Clémence (Directrice de Recherche au Lip6)
M TARISSAN Fabien (Chercheur CNRS à l'ENS Paris Saclay)
- P. Ramaciotti Morales, R. Lamarche‑Perrin, R. Fournier‑S'niehotta, R. Poulain, L. Tabourier, F. Tarissan : “Measuring Diversity in Heterogeneous Information Networks”, Theoretical Computer Science, (Elsevier) (2021)
- R. Poulain : “Analyse et modélisation de la diversité des structures relationnelles à l’aide de graphes multipartis”, thesis, defence 12/04/2020, supervision Magnien, Clémence, rapporteurs : TARISSAN Fabien (2020)
- R. Poulain, F. Tarissan : “Investigating the lack of diversity in user behavior: The case of musical content on online platforms”, Information processing & management, vol. 57 (2), pp. 102169, ([Oxford]: Elsevier Ltd.) (2020)
- M. Journault, P. Lafourcade, M. More, R. Poulain, L. Robert : “How to Teach the Undecidability of Malware Detection Problem and Halting Problem”, WISE13: The 13th World Conference on Information Security Education, Maribor, Slovenia (2020)
- R. Poulain, F. Tarissan : “Quantifying the diversity in users activity: an example study on online music platforms”, SNAMS-2018 - The Fifth International Conference on Social Networks Analysis, Management and Security, Valence, Spain, pp. 3-10, (IEEE) (2018)