Developing a social network analysis and visualization module for repast models

Dealing with social networks becomes more and more attractive to modelers. This is especially true for the field of agent-based modeling, in which represented actors are connected with others, with which they communicate, exchange goods, or spend their leisure time. While a number of software frameworks exists that ease the development of such models, the support for analyzing and visualizing social networks is still in its infancy. First, the paper identifies requirements on software that seeks to aid the handling of social networks. In contrast to software in the field of social network analysis (SNA), the dynamics of modeled networks require specific considerations. Changes in the network structure should be perceptible for the user, which makes certain demands on the layout process. Five frameworks and additional libraries are reviewed in order to find an appropriate starting point to implement the requirements worked out, and attention is also drawn to existing models that shall be extended by network features. Repast J is identified as a rich and widespread framework that is intended for social science simulations and also incorporates basic network facilities. This paper introduces the newly developed software library ReSoNetA (Repast Social Network Analysis), which adds network functionality to the Repast J framework. It uses several features of the recently released Repast Simphony framework, and extends and improves network visualization capabilities. ReSoNetA also offers an extensible network measure framework, which enables the user to compute any network measure through GUI elements, use them for analyzing the networks, and also to affect the visualization. Several network measures and network layouts are described in detail. While ReSoNetA constitutes a valuable base for analysis and visualization of social networks, the library has some potential to be developed further. Recommendations for such extensions are given. For example, providing sophisticated and efficient network layouts that preserve the viewer’s mental map, while the network structure changes during simulation is hard to achieve and needs some further investigation. Most of the ReSoNetA features were developed in line with the Repast Simphony architecture, which makes it possible to incorporate them into that recent agent-based modeling framework.