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Nudging agents in social networks for collective action 1.0.0

To increase the level of collective action to solve problems related to sustainability and public health behavioral scientists have shown that the use of social influence and peer pressure can be effective. How to nudge a small set of individuals to generate cascades of cooperation? Using a stylized agent-based model we explore how different assumptions on network structure and attributes of agents, as well as forms of feedback will influence the level of adaptation. Our analysis shows that targeting those who are most socially influenceable is more effective than those who are most or best connected in social networks.
This is a companion discussion topic for the original entry at https://www.comses.net/codebases/2587/releases/1.0.0/

Hi Marco.

I had a question re: a your code and ODD. When generating the network and calculating the link probability, d is the average network density. In the NetLogo code for this calculation, d is distance myself. It is not clear how this distance calculation corresponds to network density? Clarification of this would be greatly appreciated.

Mahalo,
Steven

Thanks Steven for your question. There was indeed a mistake in the ODD, d in the probability equation should be the distance between two nodes. I updated the ODD, and I also updated the code to Netlogo 6. You can find this in the new release 1.1.0 of the model.