Comparative Agent-Based Simulations on Levels of Multiplicity Using a Network Regression: A Mobile Dating Use-Case
Source abstract
Abstract
We demonstrate the use of agent-based models to simulate the interactions of two mobile dating applications that possess divergent interaction features. We reproduce several expected outcomes when compared to extant literature. We also demonstrate the use of a standard social network analysis technique—the network regression, Multiple Regression Quadratic Assignment Procedure—in conducting a principled and interpretable comparison between the two models with strong results. This combined approach is novel and allows complex system modelers who utilize agent-based models to reduce their reliance on idealized network structures (small world, scale-free, erdos-renyi) when applying underlying network interactions to agent-based models that can often skew results and mislead from a full picture of system-level properties. This work serves as a proof-of-concept in the integration of classical social network analysis methods and contemporary agent-based modeling to compare software designs and to enhance the policy-generation process of online social networks.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Opinion Dynamics and Social Influence · Complex Network Analysis Techniques · Social Capital and Networks
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Massive Data Institute, McCourt School of Public Policy, Georgetown University, 37th and O Streets NW, Old North, Suite 100, Washington, DC 20057, USA
Department of Computational and Data Sciences, George Mason University, 4400 University Drive, Fairfax, VA 22030, USA
Funding
Oak Ridge Associated Universities
References (93)
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