Modelling and Analysis of the Dynamics of Adaptive Temporal-Causal Network Models for Evolving Social Interactions

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Network-Oriented Modelling based on adaptive temporal-causal networks provides a unified approach to model and analyse dynamics and adaptivity of various processes, including mental and social interaction processes. Adaptive temporal-causal network models are based on causal relations by which the states in the net-work change over time, and these causal relations are adaptive in the sense that they themselves also change over time. It is discussed how modelling and analysis of the dynamics of the behaviour of these adaptive network models can be performed. The approach is illustrated for adaptive network models describing social interaction. In particular, the homophily principle and the more becomes more principles for social interactions are addressed.
LanguageEnglish
Pages1-20
Number of pages20
JournalComputational Social Networks
Volume4
Issue number4
DOIs
StatePublished - 2017

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Causal Model
Social Interaction
Network Model
Modeling
Adaptivity

Keywords

  • Adaptive Network
  • Temporal-causal network model
  • Social interaction

Cite this

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title = "Modelling and Analysis of the Dynamics of Adaptive Temporal-Causal Network Models for Evolving Social Interactions",
abstract = "Network-Oriented Modelling based on adaptive temporal-causal networks provides a unified approach to model and analyse dynamics and adaptivity of various processes, including mental and social interaction processes. Adaptive temporal-causal network models are based on causal relations by which the states in the net-work change over time, and these causal relations are adaptive in the sense that they themselves also change over time. It is discussed how modelling and analysis of the dynamics of the behaviour of these adaptive network models can be performed. The approach is illustrated for adaptive network models describing social interaction. In particular, the homophily principle and the more becomes more principles for social interactions are addressed.",
keywords = "Adaptive Network, Temporal-causal network model, Social interaction",
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Modelling and Analysis of the Dynamics of Adaptive Temporal-Causal Network Models for Evolving Social Interactions. / Treur, J.

In: Computational Social Networks, Vol. 4, No. 4, 2017, p. 1-20.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Modelling and Analysis of the Dynamics of Adaptive Temporal-Causal Network Models for Evolving Social Interactions

AU - Treur,J.

PY - 2017

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AB - Network-Oriented Modelling based on adaptive temporal-causal networks provides a unified approach to model and analyse dynamics and adaptivity of various processes, including mental and social interaction processes. Adaptive temporal-causal network models are based on causal relations by which the states in the net-work change over time, and these causal relations are adaptive in the sense that they themselves also change over time. It is discussed how modelling and analysis of the dynamics of the behaviour of these adaptive network models can be performed. The approach is illustrated for adaptive network models describing social interaction. In particular, the homophily principle and the more becomes more principles for social interactions are addressed.

KW - Adaptive Network

KW - Temporal-causal network model

KW - Social interaction

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VL - 4

SP - 1

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JO - Computational Social Networks

T2 - Computational Social Networks

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