Co-evolution in Epistemic Networks - Reconstructing Social Complex Systems
type: Dataset
contact point: Organization
  fn: CCSD
keyword: complex-systems
keyword: reconstruction
keyword: mathematical-sociology
keyword: epistemologie-appliquee
keyword: systemes-complexes
keyword: cultural-co-evolution
keyword: sociologie-mathematique
keyword: sticbibldomainsticdomainsticbibl
keyword: dynamic-social-networks
keyword: applied-epistemology
keyword: scientometrie
keyword: co-evolution-culturelle
keyword: sticsocidomainsticdomainsticsoci
keyword: reseaux-sociaux-dynamiques
keyword: galois-lattices
keyword: theses
keyword: cognition-sociale
keyword: social-cognition
keyword: decouverte-de-connaissances-dans-les-bases-de-donnees
keyword: infoeu-reposemanticsdoctoralthesis
keyword: scientometrics
keyword: taxonomies
keyword: treillis-de-galois
keyword: infoinfo-nicomputer-science-csnetworking-and-internet-architecture-csni
keyword: shssociohumanities-and-social-sciencessociology
keyword: knowledge-discovery-in-databases
landing page: https://pastel.hal.science/tel-00068958
description: Agents producing and exchanging knowledge are forming as a whole a socio-semantic complex system. Studying such knowledge communities offers theoretical challenges, with the perspective of naturalizing further social sciences, as well as practical challenges, with potential applications enabling agents to know the dynamics of the system they are participating in. The present thesis lies within the framework of this research program. Alongside and more broadly, we address the question of reconstruction in social science. Reconstruction is a reverse problem consisting of two issues: (i) deduce a given high-level observation for a considered system from low-level phenomena; and (ii) reconstruct the evolution of high-level observations from the dynamics of lower-level objects. In this respect, we argue that several significant aspects of the structure of a knowledge community are primarily produced by the co-evolution between agents and concepts, i.e. the evolution of an epistemic network. In particular, we address the first reconstruction issue by using Galois lattices to rebuild taxonomies of knowledge communities from low-level observation of relationships between agents and concepts; achieving ultimately an historical description (inter alia field progress, decline, specialization, interaction - merging or splitting). We then micro-found various stylized facts regarding this particular structure, by exhibiting processes at the level of agents accounting for the emergence of epistemic community structure. After assessing the empirical interaction and growth processes, and assuming that agents and concepts are co-evolving, we successfully propose a morphogenesis model rebuilding relevant high-level stylized facts. We finally defend a general epistemological point related to the methodology of complex system reconstruction, eventually supporting our choice of a co-evolutionary framework.
issued: 2026-05-21T07:55:26.257439
language: en
modified: 2026-05-21T07:55:26.257447

Co-evolution in Epistemic Networks - Reconstructing Social Complex Systems
type: Distribution
access URL: https://pastel.hal.science/tel-00068958
format: HTML
issued: 2026-05-21T07:55:26.440845
modified: 2026-05-21T07:55:26.184809

test_moissonnage_selune
type: Agent