Computational Modelling of Trust and Social Relationships
Bibliographic Data
| ID | 7516500 |
|---|---|
| Authors | Alistair Sutcliffe (0000-0002-7955-2232, corresponding author), Di Wang (0000-0002-7338-3351) |
| Year | 2012 |
| Volume | 15 |
| Issue | 1 |
| Publication date | 2012-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Artificial Societies and Social Simulation (JOURNAL) |
| Journal identifiers | ISSN: 1460-7425 • E-ISSN: 1460-7425 |
| Publisher | Journal of Artificial Societies and Social Simulation (PUBLISHER) |
| DOI | 10.18564/jasss.1912 |
| OpenAlex | W2143600447 |
| Language | EN |
| Citations received | 3 |
| References cited | 21 |
A computational model for the development of social relationships is described. The model implements agent strategies for social interaction based on Dunbar's Social Brain Hypothesis (SBH). A trust related process controls the formation and decay of relationships as a function of interaction frequency, the history of interaction, and the agents' strategies. A good fit the SBH predictions was found across a range of model parameter settings, which varied the waning rate of trust, defect/cooperation rates for agents, and linear/log functions for trust increase and decay. Social interaction strategies which favour interacting with existing strong ties or a time variant strategy produced more SBH conformant results than strategies favour more weaker relationships. The prospects for modeling the emergence of social relationships are discussed
Data science · Cognitive Science and Mapping · Complex Network Analysis Techniques · Computer Science · Opinion Dynamics and Social Influence
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| Unique citing works | 3 |
|---|---|
| Citations per year | 0,21 |
| Citation span | 2012 - 2015 (4) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 3 |