Social Norms As Connections: An Agent-Based Model to Understand Changes in Social Network Dynamics

The present study aims to investigate how to find changes in social behavior patterns, combining analysis of social networks and agent-based models. The research takes the concept of norms as reference to discuss the methodological limits of the analysis of social networks for the understanding of emerging social phenomena. Social network analysis provides analytical resources for measure connections among agents, but it is not the best tool for the perception of emerging social patterns. On the other hand, agent-based models can become entangled in unnecessary details when applied to identify social action patterns. Agent-based models facilitate the construction of emerging systems, but have limitations for modeling dynamic interconnections between agents. These limits can be enhanced when combining social network analysis and agent-based models, having the idea of norms as conceptual reference to understand the emerging phenomenon. The research developed an Netlogo agent-based model with analytical parameters of social networks to check the possibilities of identifying patterns of change in social norms simulation. The paper first reviews the different concepts of social norms and their applicability to computational sociology. Argues mainly with the BDI models. The second part is the exposition of the agent-based model combined with social networks parameters. The results expect to contribute methodologically to studies about the emergence of complex social phenomena and the identification of patterns of social change.