Wouter de Nooy

Exploratory Social Network Analysis with Pajek: List of Illustrations

This is an extensively revised and expanded second edition of the successful textbook on social network analysis integrating theory, applications, and network analysis using Pajek. The main structural concepts and their applications in social research are introduced with exercises. Pajek software and data sets are available so readers can learn network analysis through application and case studies. Readers will have the knowledge, skill, and tools to apply social network analysis across the social sciences, from anthropology and sociology to business administration and history. This second edition has a new chapter on random network models, for example, scale-free and small-world networks and Monte Carlo simulation; discussion of multiple relations, islands, and matrix multiplication; new structural indices such as eigenvector centrality, degree distribution, and clustering coefficients; new visualization options that include circular layout for partitions and drawing a network geographically as a 3D surface; and using Unicode labels. This new edition also includes instructions on exporting data from Pajek to R software. It offers updated descriptions and screen shots for working with Pajek (version 2.03).

Fields and networks: correspondence analysis and social network analysis in the framework of field theory

Pierre Bourdieu advocated relational thinking and a relational methodology. Nevertheless, he rejected social network analysis as a suitable technique for analyzing fields and he prescribed correspondence analysis. There are no fundamental technical differences between the two methods: social network analysis can produce spatial diagrams that are very similar to correspondence maps. Bourdieus problem with network analysis concerns the kind of relations that should be analyzed: objective relations instead of the interpersonal relations usually studied in social network analysis. This paper discusses the differences between the two types of relations and it argues that interpersonal relations mediate and transform the effect of objective relations. Network analysis is needed for investigating this process, which may help to further integrate Bourdieus field theory and theory of practice.

The dynamics of artistic prestige

Artistic careers and artistic prestige are dynamically linked: artists and art institutions derive their prestige from their past successes (trajectories), and their present prestige influences the further course of their careers. In addition, the prestige of artists and institutions are intertwined. Artists derive their prestige at least in part from their affiliations to art organizations, and the prestige of organizations is based on the artists which they are able to take on. This paper introduces a simple but efficient index to measure dynamic prestige from a longitudinal network of affiliations. It is shown that the prestige of literary magazines can be computed from the flow of authors between magazines and that it correlates strongly with external indicators of literary prestige. An advanced method for analyzing longitudinal networks was used to demonstrate that this index of prestige predicts the exchange of authors between magazines whereas static indices of prestige do not. The results corroborate the relational and dynamic character of positions within the literary field postulated in the field theory of Pierre Bourdieu.

Networks of action and events over time: a multilevel discrete-time event history model for longitudinal network data

Longitudinal network data recording the moment at which ties appear, change, or disappear are increasingly available. Event history models can be used to analyze the dynamics of time-stamped network data. This paper adapts the discrete-time event history model to social network data. A discrete-time event history model can easily incorporate a multilevel design and time-varying covariates. A multilevel design is needed to account for dependencies among ties and vertices, which should not be ignored in a small longitudinal network. Time-varying covariates are required to analyze network effects, that is, the impact of previous ties. In addition, a discrete-time event history model handles constraints on who can act or who can be acted upon in a straightforward way. The model can be estimated with multilevel logistic regression analysis, which is illustrated by an application to book reviews, so network evolution can be analyzed with a fairly standard statistical tool.

Innovation as a nonlinear process, the scientometric perspective, and the specification of an ‘innovation opportunities explorer’

The process of innovation follows nonlinear patterns across the domains of science, technology, and the economy. Novel bibliometric mapping techniques can be used to investigate and represent distinctive, but complementary perspectives on the innovation process (e.g. ‘demand’ and ‘supply’) as well as the interactions among these perspectives using animations. In a map, the different perspectives can be represented as ‘continents’ of data related to varying extents over time. For example, the different branches of Medical Subject Headings (MeSH) in the Medline database provide sources of such perspectives (e.g. ‘Diseases’ vs ‘Drugs and Chemicals’). The multiple-perspective approach enables us to reconstruct facets of the dynamics of innovation, in terms of selection mechanisms shaping localisable trajectories and/or resulting in more globalised regimes. By expanding the data with patents and scholarly publications, we demonstrate the use of this multi-perspective approach in the case of RNA Interference (RNAi). The possibility to develop an ‘Innovation Opportunities Explorer’ is specified.

Aggregated journal-journal citation relations in scopus and web of science matched and compared in terms of networks, maps, and interactive overlays

We compare the network of aggregated journal–journal citation relations provided by the Journal Citation Reports (JCR) 2012 of the Science Citation Index (SCI) and Social Sciences Citation Index (SSCI) with similar data based on Scopus 2012. First, global and overlay maps were developed for the 2 sets separately. Using fuzzy‐string matching and ISSN numbers, we were able to match 10,524 journal names between the 2 sets: 96.4% of the 10,936 journals contained in JCR, or 51.2% of the 20,554 journals covered by Scopus. Network analysis was pursued on the set of journals shared between the 2 databases and the 2 sets of unique journals. Citations among the shared journals are more comprehensively covered in JCR than in Scopus, so the network in JCR is denser and more connected than in Scopus. The ranking of shared journals in terms of indegree (i.e., numbers of citing journals) or total citations is similar in both databases overall (Spearman rank correlation ρ > 0.97), but some individual journals rank very differently. Journals that are unique to Scopus seem to be less important—they are citing shared journals rather than being cited by them—but the humanities are covered better in Scopus than in JCR.

Communication in natural resource management: agreement between and disagreement within stakeholder groups

Communication among stakeholders is commonly held to improve agreement on facts and management goals. Results from statistical network analyses of six natural resource management systems indicate that the effects of communication depend on context. If communication affects stakeholder knowledge and values, it fosters agreement between stakeholder groups but it results in more disagreement within stakeholder groups. In addition, more centralized communication networks have more disagreement, especially within stakeholder groups, while co-management systems have more disagreement between stakeholder groups. The results may reflect communication effects but also selection effects: the propensity of stakeholders or management systems to establish communication ties between participants with dissimilar knowledge and values. In addition, the results may be linked to different phases in the management process. The conclusion includes a reflection on the need for further research to address these possibilities.

The sign of affection. Balance-theoretic models and incomplete signed digraphs

Abstract The initial structural models based on balance theory (structural balance and clusterability) dealt with incomplete signed digraphs. However, newer models (ranked clusters, transitivity, hierarchical M -cliques) apply only to zero-one matrices representing either unsigned digraphs or complete signed digraphs. Since empirical networks of affective relations are signed but seldom complete — actors may have neutral feelings towards alters or affections may be unknown to the researcher — the latter models must be redefined if affective relations are to be analysed. It was found that each balance-theoretic model is characterised by a particular type of semicycle or path. Counts of the types of semicycles and paths suffice to identify the models. This approach is more general than triadic analysis because it handles complete as well as incomplete signed digraphs.

The dynamics of triads in aggregated journal-journal citation relations: specialty developments at the above-journal level

Dyads of journals—related by citations—can agglomerate into specialties through the mechanism of triadic closure. Using the Journal Citation Reports 2011, 2012, and 2013, we analyze triad formation as indicators of integration (specialty growth) and disintegration (restructuring). The strongest integration is found among the large journals that report on studies in different scientific specialties, such as PLoS ONE, Nature Communications, Nature, and Science. This tendency toward large-scale integration has not yet stabilized. Using the Islands algorithm, we also distinguish 51 local maxima of integration. We zoom into the cited articles that carry the integration for: (i) a new development within high-energy physics and (ii) an emerging interface between the journals Applied Mathematical Modeling and the International Journal of Advanced Manufacturing Technology. In the first case, integration is brought about by a specific communication reaching across specialty boundaries, whereas in the second, the dyad of journals indicates an emerging interface between specialties. These results suggest that integration picks up substantive developments at the specialty level. An advantage of the bottom-up method is that no ex ante classification of journals is assumed in the dynamic analysis.

Structure from interaction events

In this contribution to the colloquium, I argue why and how I lost interest in the overall structure of social networks even though Big Data techniques are increasingly simplifying the collection, organisation, and analysis of ever larger networks. The challenge that Big Data techniques pose to the social scientist, I think, is of a different nature. Big Data on social actors mainly record events, e.g. interactions between human beings that happen at a point in time. In contrast, social network analysts tend to think in terms of social relations that exist over a timespan. The challenge, then, is to rethink our conceptions and models of social relations and social structure. I conceptualize social structure and social relations as forces. I propose modelling these forces with regression models for longitudinal interaction data.In this contribution to the colloquium, I argue why and how I lost interest in the overall structure of social networks even though Big Data techniques are increasingly simplifying the collection, organisation, and analysis of ever larger networks. The challenge that Big Data techniques pose to the social scientist, I think, is of a different nature. Big Data on social actors mainly record events, e.g. interactions between human beings that happen at a point in time. In contrast, social network analysts tend to think in terms of social relations that exist over a timespan. The challenge, then, is to rethink our conceptions and models of social relations and social structure. I conceptualize social structure and social relations as forces. I propose modelling these forces with regression models for longitudinal interaction data.