AI Summary & Key Takeaways
AI InsightResults of the simulations show that minority or majority, group pressure, and loyalty are highly effective in norm shifting.
📌 3 Key Takeaways
Abstract
This paper aims to explain how norms change in the social world through agent-based modelling. Norms are rules, the roots of which lie in society to guide people to perform expected behaviours. Norms exist as sui generis in societies; however, they are improved and transformed by individuals in time. While norms are rather salient for some behaviours, they are subtle for others. The plurality of norms is one of the reasons for this ambiguity. Norm plurality occurs in societies where groups that have different norms for the same behaviour live together and interact constantly. Beyond that, norm differences are the basis on which different groups are defined. How do people change the norms that are already adopted, or how do adopted norms shift to opposite ones? This paper tries to explain norm shifts when there is more than one norm for a specific behaviour in an artificial society in accordance with certain factors: the minority/majority group’s norm, group pressure, and loyalty of the individual. Agent-based modelling is a useful tool to understand the social world and create an artificial one. Agents shift their norms to interact with other agents. Results of the simulations show that minority or majority, group pressure, and loyalty are highly effective in norm shifting.