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.
| Original language | English |
|---|---|
| Article number | 4 |
| Pages (from-to) | 1-20 |
| Number of pages | 20 |
| Journal | Computational Social Networks |
| Volume | 4 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 10 Reduced Inequalities
Keywords
- Adaptive Network
- Social interaction
- Temporal-causal network model
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