Exploring the Impact of Socio-Technical Core-Periphery Structures in Open Source Software Development

In this paper we apply the social network concept of core-periphery structure to the sociotechnical structure of a software development team. We propose a socio-technical pattern that can be used to locate emerging coordination problems in Open Source projects. With the help of our tool and method called TESNA, we demonstrate a method to monitor the socio-technical core-periphery movement in Open Source projects. We then study the impact of different core-periphery movements on Open Source projects. We conclude that a steady core-periphery shift towards the core is beneficial to the project, whereas shifts away from the core are clearly not good. Furthermore, oscillatory shifts towards and away from the core can be considered as an indication of the instability of the project. Such an analysis can provide developers with a good insight into the health of an Open Source project. Researchers can gain from the pattern theory, and from the method we use to study the core-periphery movements

Animating the development of Social Networks over time using a dynamic extension of multidimensional scaling

The animation of network visualizations poses technical and theoretical challenges. Rather stable patterns are required before the mental map enables a user to make inferences over time. In order to enhance stability, we developed an extension of stress-minimization with developments over time. This dynamic layouter is no longer based on linear interpolation between independent static visualizations, but change over time is used as a parameter in the optimization. Because of our focus on structural change versus stability the attention is shifted from the relational graph to the latent eigenvectors of matrices. The approach is illustrated with animations for the journal citation environments of Social Networks, the (co-)author networks in the carrying community of this journal, and the topical development using relations among its title words. Our results are also compared with animations based on PajekToSVGAnim and SoNIA

Robust Detection of Hierarchical Communities from Escherichia coli Gene Expression Data

Determining the functional structure of biological networks is a central goal of systems biology. One approach is to analyze gene expression data to infer a network of gene interactions on the basis of their correlated responses to environmental and genetic perturbations. The inferred network can then be analyzed to identify functional communities. However, commonly used algorithms can yield unreliable results due to experimental noise, algorithmic stochasticity, and the influence of arbitrarily chosen parameter values. Furthermore, the results obtained typically provide only a simplistic view of the network partitioned into disjoint communities and provide no information of the relationship between communities. Here, we present methods to robustly detect coregulated and functionally enriched gene communities and demonstrate their application and validity for Escherichia coli gene expression data. Applying a recently developed community detection algorithm to the network of interactions identified with the context likelihood of relatedness (CLR) method, we show that a hierarchy of network communities can be identified. These communities significantly enrich for gene ontology (GO) terms, consistent with them representing biologically meaningful groups. Further, analysis of the most significantly enriched communities identified several candidate new regulatory interactions. The robustness of our methods is demonstrated by showing that a core set of functional communities is reliably found when artificial noise, modeling experimental noise, is added to the data. We find that noise mainly acts conservatively, increasing the relatedness required for a network link to be reliably assigned and decreasing the size of the core communities, rather than causing association of genes into new communities.Comment: Due to appear in PLoS Computational Biology. Supplementary Figure S1 was not uploaded but is available by contacting the author. 27 pages, 5 figures, 15 supplementary file

Social Networks of Researchers in Business To Business Marketing: A Case Study of the IMP Group 1984-1999

Science is a social process that functions through social networks of researchers that form invisible colleges. Analysis of these social networks provides a means for examining the structure of relations among researchers. The Industrial Marketing and Purchasing (IMP) group, "an informal international group of scholars concerned with developing concepts and knowledge in the field of business-to-business marketing and purchasing," is used as a case study of a network of researchers because it has been responsible for considerable research over the last decades in the area of business-to-business marketing, yet its structure remains hidden because of its informal network characteristics. The results of a social network analysis of the IMP group is described based on the pattern of co-authorship at annual IMP conferences. The results reveal a power law distribution of paper co-authorship and a small world network that conforms to the results of studies of other types of social networks. A core network of 57 researchers is identified and its network properties are described, including how it has evolved over time. The study provides the basis for further studies of the social networks of marketing and business researchers.informal networks, business-to-business marketing

Visualization of scientific co-authorship in Spanish universities: from regionalization to internationalization

Purpose – To visualize the inter-university and international collaboration networks generated by Spanish universities based on the co-authorship of scientific articles. Design/methodology/approach - Formulation based on a bibliometric analysis of Spanish university production from 2000 to 2004 as contained in Web of Science databases, applying social network visualization techniques. The co-authorship data used were extracted with the total counting method from a database containing 100,710 papers. Findings – Spanish inter-university collaboration patterns appear to be influenced by both geographic proximity and administrative and political affiliation. Inter-regional co-authorship encompasses regional sub-networks whose spatial scope conforms rather closely to Spanish geopolitical divisions. Papers involving international collaboration are written primarily with European Union and North and Latin American researchers. Greater visibility is attained with international co-authorship than any other type of collaboration studied. Research limitations/implications - Impact was measured in terms of journals rather than each individual article. The co-authorship data were taken from the Web of Knowledge and were not compared to data from other databases. Practical implications - The data obtained may provide guidance for public policy makers seeking to enhance and intensify the internationalization of scientific production in Spanish universities. Originality – The Spanish university system is in the midst of profound structural change. This is the first article to describe Spanish university collaboration networks using social network visualization techniques, covering an area not previously addressed.Publicad

Brokering the core and the periphery: Creative success and collaboration networks in the film industry

In collaboration-based creative industries, such as film production, creators in the network core enjoy prestige and legitimacy that are key for creative success. However, core creators are challenged to maintain diverse access to new ideas or alternative views that often emerge from the network periphery. In this paper, we demonstrate that creators in the network core can increase the probability of their creative success by brokering peripheral collaborators to the core. The argument is tested on a dynamic collaboration network of movie creators constructed from a unique dataset of Hungarian feature films for the 1990-2009 period. We propose a new way to capture brokers' role in core/periphery networks and provide evidence that being in the core and at the same time bridging between the core and the periphery of the network significantly increases the likelihood of award winning

The Sixth Framework Program as an Affiliation Network: Representation and Analysis

In this paper, we compare two different representations of Framework Programs as affiliation network: “One-mode networks”' and “Two-mode networks”'. The aim of this article is to show that the choice of the representation has an impact on the analysis of the networks and on the results of the analysis. In order to support our proposals, we present two forms of representation and different indicators used in the analysis. We study the network of the 6th Framework Program using the two forms of representation. In particular, we show that the identification of the central nodes is sensitive to the chosen representation. Furthermore, the nodes forming the core of the network vary according to the representation. These differences of results are important as they can influence innovation policies.Affiliation Network, Innovation Policies, Centrality

Affiliation network: representations and analysis

In this paper, we compare two different representations of Framework Programs as affiliation network: “One-mode networks” and “Two-mode networks”. The aim of this article is to show that the choice of the representationhas an impact on the analysis of the networks and on the results of the analysis. In order to support our proposals, we present two forms of representation and different indicators used in the analysis. We study the network of the 6th Framework Program using the two forms of representation. In particular, we show that the identification of the central nodes is sensitive to the chosen representation. Furthermore, the nodes forming the core of the network vary according to the representation. These differences of results are important as they can influence innovation policies.networks