BOURIGAULT Simon
Supervision : Patrick GALLINARI
Co-supervision : LAMPRIER Sylvain
Apprentissage de la dynamique de propagation d'info dans les réseaux sociaux
In this thesis, we study information diffusion in online social networks. Websites like Facebook or Twitter have indeed become information medias, on which users create and share a lot of data. Most existing models of the information diffusion phenomenon relies on strong hypothesis about the structure and dynamics of diffusion. In this document, we study the problem of diffusion prediction in the context where the social graph is unknown and only user actions are observed.
- We propose a learning algorithm for the independant cascades model that does not take time into account. Experimental results show that this approach obtains better results than time-based learning schemes.
- We then propose several representations learning methods for this task of diffusion prediction. This let us define more compact and faster models.
- Finally, we apply our representation learning approach to the source detection task, where it obtains much better results than graph-based approaches.
Defence : 11/10/2016
Jury members :
M. Fabrice Rossi, Paris 1 Panthéon Sorbonne [Rapporteur]
M. Julien Velcin, Université Lumière Lyon 2 [Rapporteur]
Mme. Christine Largeron, Université Jean Monnet
M. Christophe Marsala, Université Pierre et Marie Curie
M. Sylvain Lamprier, Université Pierre et Marie Curie
M. Patrick Gallinari , Université Pierre et Marie Curie
2014-2017 Publications
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2017
- S. Bourigault, S. Lamprier, P. Gallinari : “Apprentissage de reprĂ©sentation pour la dĂ©tection de source dans les rĂ©seaux sociaux”, COnfĂ©rence en Recherche d'Informations et Applications - CORIA 2017, 14th French Information Retrieval Conference, Marseille, France, pp. 235-250 (2017)
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2016
- S. Bourigault : “Apprentissage de la dynamique de propagation d’info dans les rĂ©seaux sociaux”, thesis, defence 11/10/2016, supervision Gallinari, Patrick, co-supervision : Lamprier, Sylvain (2016)
- S. Bourigault, S. Lamprier, P. Gallinari : “Learning Distributed Representations of Users for Source Detection in Online Social Networks”, ECML PKDD 2016 - European Conference on Machine Learning and Knowledge Discovery in Databases, vol. 9852, Lecture Notes in Computer Science, Riva del Garda, Italy, pp. 265-281, (Springer) (2016)
- S. Bourigault, S. Lamprier, P. Gallinari : “Apprentissage de ReprĂ©sentations Probabilistes pour la PrĂ©diction de Diffusions d’Informations sur les RĂ©seaux Sociaux”, COnfĂ©rence en Recherche d'Information et Applications 2016 (CORIA), Toulouse, France, pp. 89-104 (2016)
- S. Bourigault, S. Lamprier, P. Gallinari : “Representation Learning for Information Diffusion through Social Networks: an Embedded Cascade Model”, International Conference on Web Search and Data Mining, San Francisco, United States, pp. 573-582, (ACM) (2016)
- S. Lamprier, S. Bourigault, P. Gallinari : “Influence learning for cascade diffusion models: focus on partial orders of infections”, Social Network Analysis and Mining, vol. 6 (1), pp. 93, (Springer) (2016)
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2015
- S. Lamprier, S. Bourigault, P. Gallinari : “Extracting Diffusion Channels from Real-World Social Data: a Delay-Agnostic Learning of Transmission Probabilities”, International Conference on Advances in Social Networks Analysis and Mining 2015, Paris, France (2015)
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2014
- S. Bourigault, C. Lagnier, S. Lamprier, L. Denoyer, P. Gallinari : “Apprentissage de reprĂ©sentation pour la diffusion d’Information dans les rĂ©seaux sociaux”, COnfĂ©rence en Recherche d'Information et Applications 2014, CORIA 2014, Nancy, France, pp. 155-170 (2014)
- S. Bourigault, C. Lagnier, S. Lamprier, L. Denoyer, P. Gallinari : “Learning social network embeddings for predicting information diffusion”, Proceedings of the 7th ACM international conference on Web search and data mining, New York, United States, pp. 393-402, (ACM) (2014)
- C. Lagnier, S. Bourigault, S. Lamprier, L. Denoyer, P. Gallinari : “Learning Information Spread in Content Networks”, ICLR 2014 - International Conference on Learning Representations, CoRR, Banff, Canada, pp. abs/1312.6169 (2014)