Dynamic Models of Affiliation and the Network Structure of Problem Solving in an Open Source Software Project

Abstract

Two-mode networks are used to describe dual patterns of association between distinct social entities through their joint involvement in categories, activities, issues, and events. In empirical organizational research, the analysis of two-mode networks is typically accomplished either by (a) decomposition of the dual structure into its two unimodal components defined in terms of indirect relations between entities of the same kind or (b) direct statistical analysis of individual two-mode dyads. Both strategies are useful, but neither is fully satisfactory. In this article, the authors introduce newly developed stochastic actor-based models for two-mode networks that may be adopted to redress the limitations of current analytical strategies. The authors specify and estimate the model in the context of data they have collected on the dual association between software developers and software problems observed during a complete release cycle of an open source software project. The authors discuss the general methodological implications of the models for organizational research based on the empirical analysis of two-mode networks.

A Stochastic Actor-Based Modelling of the Evolution of an Intercity Corporate Network

“…For example, information about network paths of length three or more and/or about nodes with a single connection are lost in the transformation (Wang et al, 2009;Conaldi et al, 2012). Furthermore, the network projection usually creates densely connected one-mode networks (Opsahl, 2012), making it difficult to differentiate network clusters that are generated from generic underlying networking processes from those generated by the network projection itself (Latapy et al, 2008).…”

“…Recently developed exponential random graph modelling (ERGM) for two-mode networks (Wang et al 2009; offer a possible solution to this interdependence issue in the intercity corporate network, as the ERGM model (1) examines the two-mode network relationships directly, and (2) allows to test different local dependence processes underlying observed networks. Nevertheless, to date ERGMs for two-mode networks are only capable of handling cross-sectional data (Conaldi et al, 2012), and can only be interpreted at (macro-)network level (Desmarais and Cranmer, 2011).…”

Exploring the co-evolution of the geographies of air transport aviation and corporate networks

“…The validity of stochastic actor-based models can be assessed by comparing observed networks with networks that are simulated from the proposed model, i.e., measuring goodness-of-fit (Snijders et al, 2009;Conaldi et al, 2012). Smaller divergences between the observed and simulated networks suggest that the specified models (i.e., network effects) are more likely to capture the true underlying network mechanism, and vice versa.…”

“…Models are implemented with the RSiena package (Ripley et al 2012;Conaldi et al 2012). The goodness-of-fit measurements for our SABMs can be found in Appendix 1.…”

Using social network analysis to understand actor participation and influence on sustainable management of Rugezi wetland, Rwanda

“…For patterns of interactions among actors and arenas, interviewees were asked to choose from the list of arenas in which they participated. This allowed to construct a matrix linking the actor to arenas (Conaldi, Lomi, and Tonellato 2012). A binary code 1 was used to specify participation to the arena and 0 the absence of participation.…”