Contact Project Developer Ashish D. Tiwari [astiwz@gmail.com]
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Trust Agent-Based Behavior Induction in Social Networks

The essence of social networks is that they can influence people's public opinions and group behaviors form quickly.
Abstract-Synopsis-Documentation

Trust Agent-Based Behavior Induction in Social Networks.

ABSTRACT

The essence of social networks is that they can influence people's public opinions and group behaviors form quickly. Negative group behavior influences societal stability significantly, but existing behavior-induction approaches are too simple and inefficient. To automatically and efficiently induct behavior in social networks, this article introduces trust agents and designs their features according to group behavior features. In addition, a dynamics control mechanism can be generated to coordinate participant behaviors in social networks to avoid a specific restricted negative group behavior. This article investigates the importance of the endogenous selection of partners for trust and cooperation inmarket exchange situations, where there is informationasymmetry betweeninvestors andtrustees.We created an experimental-data driven agent-based model where the endogenous link between interaction outcome and social structure formation was examined starting from heterogeneous agent behaviour. By testing various social structure configurations, we showed that dynamic networks lead to more cooperation when agents can create more links and reduce exploitation opportunities by free riders. Furthermore, we found that the endogenous network formation was more important for cooperation than the type of network. Our results cast serious doubt about the static view of network structures on cooperation and can provide new insights into market efficiency.


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