An information‐theoretic‐based (MaxEnt) approach to social dynamical systems
| Autor: | Roberto Luzzi, Marcus V. Mesquita, Justino R. Madureira |
|---|---|
| Rok vydání: | 2001 |
| Předmět: |
Mathematical sociology
Algebra and Number Theory Sociology and Political Science Dynamical systems theory Stochastic modelling business.industry Predictive analytics Social group Social system Entropy (information theory) Artificial intelligence Statistical theory business Social Sciences (miscellaneous) Mathematics |
| Zdroj: | The Journal of Mathematical Sociology. 25:179-224 |
| ISSN: | 1545-5874 0022-250X |
| DOI: | 10.1080/0022250x.2001.9990250 |
| Popis: | Jeffreys‐Jaynes’ Predictive Statistics appears to provide a promising approach for the study of general dynamical systems. We describe an application of such theory to the analysis of the dynamics of interacting social groups. For that purpose the said statistical theory is redirected towards the construction of an equivalent stochastic theory. The working of the formalism is illustrated by applying it to a simplified case of opinion forming in a two‐candidates election. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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