Sociologie informatique

Résumé

La sociologie informatique ou sociologie computationnelle (en anglais computational sociology) est une branche de la sociologie qui consiste à utiliser le calcul pour analyser des phénomènes sociaux. Il s'agit d'utiliser la technique de la simulation sur ordinateur pour la construction de modèles sociaux. Cela implique un certain arrangement des agents sociaux, et des interactions entre eux. Enfin, on examine l'effet de ces interactions sur un agrégat social. Bien que les thèmes et les méthodologies de cette science sociale diffèrent de ceux de la science normale ou informatique, plusieurs des approches utilisées dans les simulations contemporaines du social provient des champs comme la physique et l’intelligence artificielle. Dans la littérature scientifique, la sociologie informatique est souvent liée à l'étude de complexité sociale. Concepts sociaux de complexité comme systèmes complexes, interconnexions non linéaires dans de macro et micro processus, et apparitions sont le lot

Source officielle

https://fr.wikipedia.org/wiki/Sociologie_informatique

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Publications associées (9)

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Concepts associés (16)

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Cours associés (4)

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We describe a multiscale finite element (FE) solver for elliptic or parabolic problems with highly oscillating coefficients. Based on recent developments of the so-called heterogeneous multiscale method (HMM), the algorithm relies on coupled macro- and microsolvers. The framework of the HMM allows to design a code whose structure follows the classical finite elements implementation at the macro level. To account for the fine scales of the problem, elementwise numerical integration is replaced by micro FE methods on sampling domains. We discuss a short and flexible FE implementation of the multiscale algorithm, which can accommodate simplicial or quadrilateral FE and various coupling conditions for the constrained micro simulations. Extensive numerical examples including three dimensional and time dependent problems are presented illustrating the efficiency and the versatility of the computational strategy. (C) 2009 Elsevier B.V. All rights reserved.

2009

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n this paper we illustrate the core technologies at the basis of the European SPADnet project (www.spadnet.eu), and present the corresponding first results. SPADnet is aimed at a new generation of MRI-compatible, scalable large area image sensors, based on CMOS technology, that are networked to perform gamma-ray detection and coincidence to be used primarily in (Time-of-Flight) Positron Emission Tomography (PET). The project innovates in several areas of PET systems, from optical coupling to single-photon sensor architectures, from intelligent ring networks to reconstruction algorithms. In addition, SPADnet introduced the first computational model enabling study of the full chain from gamma photons to network coincidence detection through scintillation events, optical coupling, etc.

Elsevier2014

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complexity and computational social sciences. This paper draws from explicit (phone calls, SMS messaging) and implicit (proximity sensing based on Bluetooth radio signals) interaction patterns collected via smartphones and reality mining techniques to explain the dynamics of personal interactions and relationships. We consider three real human to human interaction networks, namely physical proximity, phone communication and instant messaging. We analyze a real undergraduate community's social circles and consider various topologies, such as the interaction patterns of users with the entire community, and the interaction patterns of users within their own community. We fit distributions of various interactions, for example, showing that the distribution of users that have been in physical proximity but have never communicated by phone ts a gaussian. Finally, we consider the types of relationships for example friendships, to see whether significant differences exist in their interaction patterns. We find statistically significant differences in the physical proximity patterns of people who are mutual friends and people who are non-mutual (or asymmetric) friends, though this difference does not exist between mutual friends and never friends, nor does it exist in their phone communication patterns. Our findings impact a wide range of data-driven applications in socio-technical systems by providing an overview of community interaction patterns which can be used for applications such as epidemiology, or in understanding the diffusion of opinions and relationships.

2012

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