Generate country-scale networks of interaction from scattered statistics
| Autor: | Thiriot, Samuel, Kant, Jean-Daniel |
|---|---|
| Přispěvatelé: | Systèmes Multi-Agents (SMA), Laboratoire d'Informatique de Paris 6 (LIP6), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Publications, Lip6 |
| Jazyk: | angličtina |
| Rok vydání: | 2008 |
| Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences J.4 I.6 G.3 Computer Science - Multiagent Systems Computer Science - Social and Information Networks Applications (stat.AP) [INFO]Computer Science [cs] [INFO] Computer Science [cs] Statistics - Applications Multiagent Systems (cs.MA) |
| Zdroj: | ESSA 2008, European Social Simulation Association Conference ESSA 2008, European Social Simulation Association Conference, Sep 2008, Brescia, Italy |
| Popis: | It is common to define the structure of interactions among a population of agents by a network. Most of agent-based models were shown highly sensitive to that network, so the relevance of simulation results directely depends on the descriptive power of that network. When studying social dynamics in large populations, that network cannot be collected, and is rather generated by algorithms which aim to fit general properties of social networks. However, more precise data is available at a country scale in the form of socio-demographic studies, census or sociological studies. These "scattered statistics" provide rich information, especially on agents' attributes, similar properties of tied agents and affiliations. In this paper, we propose a generic methodology to bring up together these scattered statistics with bayesian networks. We explain how to generate a population of heterogeneous agents, and how to create links by using both scattered statistics and knowledge on social selection processes. The methodology is illustrated by generating an interaction network for rural Kenya which includes familial structure, colleagues and friendship constrained given field studies and statistics. Comment: 12 pages. arXiv admin note: substantial text overlap with arXiv:2003.02213 |
| Databáze: | OpenAIRE |
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