Interpreting Nestedness and Modularity Structures in Affiliation Networks: An Application in Knowledge Networks Formed by Software Project Teams

An understanding of the knowledge creation and diffusion process in the organizational context is extremely relevant. Because from this understanding, organizations can restructure processes, reorient teams and implement methodologies to assist in the construction of an evolutionary process of knowledge creation and diffusion aimed at sustainable growth and innovation. The theory of complex social networks has been applied in several fields to help understand organizational cognitive processes. However, these approaches still insipiently consider the analysis of the nestedness and modularity of the studied networks. In this article, we presented an approach that sought to identify patterns of nestedness and modularity in networks of affiliation of people in projects in the organizational context. The study sought to identify these patterns in affiliation networks in a public organization providing information technology services in the period from 2006 to 2013. The detection of these patterns was performed using the NODF (Nestedness metric based on Overlap and Decreasing Fill) algorithm described by [1]. The nestedness and modularity metrics can influence patterns of knowledge creation and diffusion in formal and informal networks constituted for the execution of projects in organizations. This study showed that the network structures of the organization during the study period presented a high degree of nestedness, and it was possible to identify combined structures of nestedness and modularity.

Dynamics of Knowledge in Software Project Development Environments: An Approach Using Affiliation Networks

This work presents an approach to study the diffusion of knowledge in software development project teams based on the formation of complex social network structures in a public organization that offers information and communication technology services. We collected historical data on the allocation and records of hours worked by people in projects to build an affiliation network. We applied the method of reflections to analyze the data obtained. The constructed model enabled the description of the participation of project team members from the perspective of the creation and diffusion of knowledge in affiliation networks that describe the participation of people in projects, mediated by the knowledge and the capabilities developed for the execution of these projects. A contribution of this work is the construction of indicators related to the process of creation and diffusion of knowledge in the context of the execution of software development and maintenance projects, based on the concepts of diversification and ubiquity applied to the process of knowledge diffusion;an additional contribution is the presentation of an application of the method of reflections in an organizational context applied to the creation and diffusion of knowledge. We found that the application of management models associated with the collaborative method applied to the project development process contributed to the joint growth of diversified and more specialized knowledge alongside the knowledge considered more generic and ubiquitous. Our results show that contrary to previous expectations based on assumptions established at the beginning of the study, we concluded that in six of the seven subnetworks obtained in the period between 2007 and 2013, knowledge based on complex and diversified capabilities showed a growth proportional to the growth of knowledge related to the capabilities necessary to more general and ubiquitous activities.

Subset Multiple Correspondence Analysis as a Tool for Visualizing Affiliation Networks

In this paper we investigate the potential of Subset Multiple Correspondence Analysis (s-MCA), a variant of MCA, to visually explore two-mode networks. We discuss how s-MCA can be useful to focus the analysis on interesting subsets of events in an affiliation network while preserving the properties of the analysis of the complete network. This unique characteristic of the method is also particularly relevant to address the problem of missing data, where it can be used to partial out their influence and reveal the more substantive relational patterns. Similar to ordinary MCA, s- MCA can also alleviate the problem of overcrowded visualizations and can effectively identify associations between observed relational patterns and exogenous variables. All of these properties are illustrated on a student course-taking affiliation network.

East Asian Regional Cooperation Network and China’s Path Choice

The current East Asian regional cooperation framework is a complex system with multiple fields,levels,and players.In terms of social network theory and analysis,the East Asian regional cooperation framework can be defined as an affiliation network of cooperative mechanisms and players.Combing through the process of East Asian regional cooperation and constructing an East Asian regional cooperation network on the basis of the affiliation network model shows that the network has distinct characteristics in terms of cooperation mechanisms,cooperation entities,inter-entity relations,and the interaction of various fields of cooperation.These characteristics are apparent in concentrated form in the dynamics and limitations of East Asian regional cooperation networks.Describing and analyzing the structure and characteristics of the regional cooperation network of the Association of Southeast Asian Nations(ASEAN)can help us conduct a comprehensive examination of the current regional cooperation framework,grasp the developmental prospects of East Asian regional cooperation,and provide reference material for China's path choice in the process of future regional cooperation.