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Conférenciers invités

Guy Melançon (Université de Bordeaux) - Analyse prospective de réseaux

La présentation relatera un retour d'expérience d'un projet pluri-disciplinaire où les approches de modélisation et de visualisation des données sont mises au défi de l'accompagnement du travail de terrain (lors de la collecte de données et de la construction de réseaux - qu'il s'agit d'observer). La présentation donnera l'occasion de souligner la pertinence des réseaux multi-couches pour capturer la complexité des données à collecter, et des bases de données de graphe comme contenant apportant toute la plasticité nécessaire à l'exercice.

Gianluca Manzo (CNRS) - Complex contagions and the diffusion of innovations: Evidence from a small-N case study

Granovetter’s classic thesis on the strength of weak ties states that single exposure through long-range ties facilitates the circulation of “whatever is to be diffused”. Recent literature on “complex contagions” qualifies this statement and argues that, when the actors’ choice requires confirmation from multiple exposures, it is the structure of strong ties that really matters. The paper contributes to this debate reporting on a small-N study that relies on a unique combination of ethnographic data, social network analysis, and computational models. In particular, we investigate two rural populations of Indian and Kenyan potters who have to decide whether adopting new, objectively more efficient and economically more attractive, technical/stylistic options. Qualitative field data show that, despite common contextual factors, religious sub-communities within the Indian and Kenyan populations exhibit markedly different diffusion rates and speed over the last thirty years. To account for these differences, we first analyze empirically observed advice and kinship networks, and, then, we recreate the actual aggregate diffusion curves through a series of empirically-calibrated agent-based simulations. Combining the two methods, we show that, while single exposures through heterophilious weak ties were sufficient to initiate the diffusion process, larger bridges made of strong ties can in fact lead to faster or slower diffusion depending on actors’ initial beliefs. We conclude that, even in presence of “complex contagions”, dense local ties cannot be regarded as a sufficient condition for faster diffusion.

Eric Fleury (ENS de Lyon) - Socioeconomic dependencies of linguistic patterns in Twitter: a multivariate analysis

Our usage of language is not solely reliant on cognition but is arguably determined by myriad external factors leading to a global variability of linguistic patterns. This issue, which lies at the core of sociolinguistics and is backed by many small-scale studies on face-to-face communication, is addressed here by constructing a dataset combining the largest French Twitter corpus to date with detailed socioeconomic maps obtained from national census in France. We show how key linguistic variables measured in individual Twitter streams depend on factors like socioeconomic status, location, time, and the social network of individuals. We found that (i) people of higher socioeconomic status,  active to a greater degree during the daytime, use a more standard language; (ii) the southern part of the country is more prone to using more standard language than the northern one, while locally the used variety or dialect is determined by the spatial distribution of socioeconomic status; and (iii) individuals connected in the social network are closer linguistically than disconnected ones, even after the effects of status homophily have been removed. Our results  inform sociolinguistic theory and may inspire novel learning methods enabling the inference of socioeconomic status of people from the way they tweet.

Authors: J. Levy Abitbol, M. Karsai, J-P. Mague, J-P. Chevrot, E. Fleury