Representing dynamic social networks in discrete event social simulation
Jonathan K. Alt, Stephen Lieberman
Abstract
Jonathan K. Alt, Stephen Lieberman
Abstract
One of the key structural components of social systems is the social network. The representation of this network structure is key to providing a valid representation of the society under study. The social science concept of homophily provides a conceptual model of how social networks are formed and evolve over time. Previous work described the results of social simulation using a static homophily network. In order to gain the full benefit of modeling societies a representation of how the social network changes over time is required. This paper introduces the implementation of a dynamic homophily network, along with a case study exploring the sensitivity of model outputs to the parameters describing the network and applying social network change detection methods (SNCD) to model output.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
One of the key structural components of social systems is the social network. The representation of this network structure is key to providing a valid representation of the society under study. The social science concept of homophily provides a conceptual model of how social networks are formed and evolve over time. Previous work described the results of social simulation using a static homophily network. In order to gain the full benefit of modeling societies a representation of how the social network changes over time is required. This paper introduces the implementation of a dynamic homophily network, along with a case study exploring the sensitivity of model outputs to the parameters describing the network and applying social network change detection methods (SNCD) to model output.
Key concepts: Homophily, Social network (sociolinguistics), Computer science, Dynamic network analysis, Representation (politics), Key (lock), Social simulation, Network science