Two-mode Networks Research Articles

A Family of Affiliation Indices for Two-Mode Networks*

Abstract An affiliation network consists of actors and events. Actors are affiliated with each other by virtue of the events they mutually attend. This article introduces a family of affiliation measures that captures the extent of actors’ affiliations in the network. At one extreme, one might have an actor who attended many events, but none of these events were attended by any of the other actors in the network. Although of high degree, in no reasonable interpretation would such an actor be considered highly affiliated with other actors in the network. At the other extreme, one might have an actor defined by a collection of events, all of which were attended by another actor(s), making the actor as enmeshed in the network as possible. Most actors will be between these extremes, with some events being shared by varying others, and some not. This article introduces a family of affiliation measures based on the entries of the co-occurrence matrix. After defining the measures, the cumulative distribution function of first-order affiliation is derived and expressed as a difference of binomials.

Niches and networks: Explaining network evolution through niche formation processes

This paper uses the evolutionary perspective of Strategic Niche Management to investigate and explain the network dynamics of a collaborative innovation network. Building upon the theories of socio-technical transitions, we link macro-level network dynamics to the micro-level niche processes of vision building and experimentation. The paper describes a method to construct longitudinal two-mode affiliation networks and this method is illustrated with an analysis of the network properties of an agricultural niche in the Netherlands over a period of 15 years. Results show how a successful niche grows more connected, even when it grows in size. We found three distinct phases during which the network composition is more or less stable. Powerful actors are able to shape the composition of the network, either through providing the financial resources or through creating “legislative space” for the network to grow.

The distribution of roles and functions for upscaling and outscaling innovations in agricultural innovation systems

In this paper we use a network perspective to study the micro level of agricultural innovation systems and investigate the different roles and functions that collaborating actors have to perform to spread their innovation both horizontally and vertically. Based on a literature review, we distinguish between three separate network functions: (1) learning and knowledge co-creation, (2) upscaling and institutional entrepreneurship and (3) outscaling and innovation brokerage.We investigate how these different functions have been performed in the case of the Northern Frisian Woodlands (NFWs) in the Netherlands over a period of 17years. We have constructed the two-mode affiliation networks of the actors involved in various multidisciplinary research projects and lobbying events. We have analysed these networks using Social Network Analysis and measured the participation rates, relative degrees and the main paths through time with the Search Path Node Pairs algorithm.The results show that the three functions are not evenly distributed over all participants in an innovation network. For each of these three functions there is a small group of people that form a core group of knowledge creators, institutional entrepreneurs and innovation brokers. The analysis of the main paths through these projects and events shows the close interaction between the lobbying and knowledge co-creation functions.The ability to perform more than one innovation function over a longer period of time is extremely rare, but those people who can pull this off are very important for the success of an innovation network. This paper therefore concludes that the organisers of innovation networks should take try to organise their collaboration in such a way that it becomes easier for individuals to perform multiple roles within an innovation network.

The Analysis of Two-mode Networks - State-of-the-art Methods with Examples

Much of the network based research in the management field is based on one-mode networks, even though a large number of inter-organizational networks are two-mode networks. In empirical studies, sc...

A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice

We propose a new stochastic actor-oriented model for the co-evolution of two-mode and one-mode networks. The model posits that activities of a set of actors, represented in the two-mode network, co-evolve with exchanges and interactions between the actors, as represented in the one-mode network. The model assumes that the actors, not the activities, have agency.The empirical value of the model is demonstrated by examining how employment preferences co-evolve with friendship and advice relations in a group of seventy-five MBA students. The analysis shows that activity in the two-mode network, as expressed by number of employment preferences, is related to activity in the friendship network, as expressed by outdegrees. Further, advice ties between students lead to agreement with respect to employment preferences. In addition, considering the multiplexity of advice and friendship ties yields a better understanding of the dynamics of the advice relation: tendencies to reciprocation and homophily in advice relations are mediated to an important extent by friendship relations.The discussion pays attention to the implications of this study in the broader context of current efforts to model the co-evolutionary dynamics of social networks and individual behavior.

The dual-projection approach for two-mode networks

There have been two distinct approaches to two-mode data. The first approach is to project the data to one-mode and then analyze the projected network using standard single-mode techniques, also called the conversion method. The second approach has been to extend methods and concepts to the two-mode case and analyze the network directly with the two modes considered jointly. The direct approach in recent years has been the preferred method since it is assumed that the conversion method loses important structural information. Here we argue that this is not the case, provided both projections are used together in any analysis. We illustrate how this approach works using core/periphery, structural equivalence and centrality as examples.

Two-mode networks: the measurement of efficiency in the profiles of actors’ participation in the occasions

In two-mode networks, the analysis of centrality aims at identifying the actors that reach predominant roles and positions by participating in the observed occasions, without investigating how they do it. In this paper, we focus on the identification of the actors who reach a significant level of connection with the others on the basis of an unsteady, but efficient, profile of participation. The concept of efficiency will be formally introduced using an axiomatic system, and extended to the network of occasions, leading to the concept of power center. We will then propose two approaches to the measurement of efficiency and power centers, based on a confrontation, namely a ratio, between actors’ and occasions’ level of social proximity and number of occasions attended (for actors), or number of participants (for occasions). The level of actors’ and occasions’ social proximity will be measured using a centrality approach. Finally, we will present an empirical application to a real two-mode network, in order to practically analyze the features and properties of the proposed indexes, and to compare them with the main centrality measures.

Partitioning large signed two-mode networks: Problems and prospects

While a substantial amount of attention within social network analysis (SNA) has been given to the study of one-mode networks, there is an increasing consideration of two-mode networks. Recent research on signed networks resulted in the relaxed structural balance (RSB) approach and its subsequent extension to signed two-mode networks involving social actors and social objects. We extend this approach to large signed two-mode networks, and address the methodological issues that arise. We develop tools to partition these types of networks and compare them with other approaches using a recently collected dataset of United Nations General Assembly roll call votes. Although our primary purpose is methodological, we take the first step towards bridging Heider's structural balance theory with recent theorizing in international relations on soft balancing of power processes.

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

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 (i) decomposition of the dual structure into its two unimodal components defined in terms of indirect relations between entities of the same kind, or (ii) direct statistical analysis of individual two-mode dyads. Both strategies are useful, but neither is fully satisfactory. In this paper we introduce newly developed stochastic actor-based models for two-mode networks that may be adopted to redress the limitations of current analytical strategies. We specify and estimate the model in the context of data we have collected on the dual association between software developers and software problems observed during a complete release cycle of an open source software project. We discuss the general methodological implications of our models for organizational research based on the empirical analysis of two-mode networks.

Analyzing event stream dynamics in two-mode networks: An exploratory analysis of private communication in a question and answer community

Information about social networks can often be collected as event stream data. However, most methods in social network analysis are defined for static network snapshots or for panel data. We propose an actor oriented Markov process framework to analyze the structural dynamics in event streams. Estimated parameters are similar to what is known from exponential random graph models or stochastic actor oriented models as implemented in SIENA. We apply the methodology on a question and answer web community and show how the relevance of different kinds of one- and two-mode network structures can be tested using a new software.

Triadic closure in two-mode networks: Redefining the global and local clustering coefficients

As the vast majority of network measures are defined for one-mode networks, two-mode networks often have to be projected onto one-mode networks to be analyzed. A number of issues arise in this transformation process, especially when analyzing ties among nodes’ contacts. For example, the values attained by the global and local clustering coefficients on projected random two-mode networks deviate from the expected values in corresponding classical one-mode networks. Moreover, both the local clustering coefficient and constraint (structural holes) are inversely associated to nodes’ two-mode degree. To overcome these issues, this paper proposes redefinitions of the clustering coefficients for two-mode networks.

P2-389 Use of healthcare in a social network of men who have sex with men in Brazil

IntroductionIt is known that men access health services less frequently than women. According to WHO it is even less frequent among men who have sex with men (MSM) which increases...

Measuring the semantic integrity of scientific fields: a method and a study of sociology, economics and biophysics

The paper introduces a concept for measuring the interpretive fragmentation of scientific fields by the analysis of their citation networks. Transitive closure in two-mode networks is the basis of the proposed measurement. To test the validity of the concept two analyses are presented. One compares the integrity of two social sciences, sociology and economics, and a natural science, biophysics. The results are in line with the widely held opinion, that because of the lack in cumulative and consensual knowledge production mechanisms the social sciences are more disintegrated. Sociology is considerably more fragmented then economics, as the different paradigm structure of these disciplines would predict. As a second test, the fragmentation of scholarly communication inside and between the sub-fields of sociology is measured. The results correctly indicate that meaning making processes are taking place inside invisible colleges.

Partitioning Signed Two-Mode Networks

Structural balance theory forms the foundation for a generalized blockmodel method useful for delineating the structure of signed social one-mode networks for social actors (for example, people or nations). Heider's unit formation relation was dropped. We re-examine structural balance by formulating Heider's unit formation relations as signed two-mode data. Just as generalized blockmodeling has been extended to analyze two-mode unsigned data, we extend it to analyze signed two-mode network data and provide a formalization of the extension. The blockmodel structure for signed two-mode networks has positive and negative blocks, defined in terms of different partitions of rows and columns. These signed blocks can be located anywhere in the block model. We provide a motivating example and then use the new blockmodel type to delineate the voting patterns of the Supreme Court justices for all of their nonunanimous decisions for the 2006–07 term. Interpretations are presented together with a statement of further problems meriting attention for partitioning signed two-mode data.

Pareto-improving and revenue-neutral congestion pricing schemes in two-mode traffic networks

This paper studies a Pareto-improving and revenue-neutral congestion pricing scheme on a simple two-mode (highway and transit) network: this scheme aims at simultaneously improving system performance, making every individual user better off, and having zero total revenue. Different Pareto-improving situations are explored when a two-mode transportation system serves for travel groups with different value-of-time (VOT) distributions. Since the congestion pricing scheme suggested here charges transit users negative tolls and automobile users positive tolls, it can be considered as a proper way to implement congestion pricing and transit subsidy in one step, while offsetting the inequity for the poor. For a general VOT distribution of commuters, the condition of Pareto-improving is established, and the impact of the VOT distribution on solving the inequity issue is explored. For a uniform VOT distribution, we show that a Pareto-improving and revenue-neutral pricing scheme always exists for any target modal split pattern that reduces the total system travel time.

Exponential random graph ( [formula omitted]) models for affiliation networks

Recent advances in Exponential Random Graph Models (ERGMs), or p ∗ models, include new specifications that give a much better chance of model convergence for large networks compared with the traditional Markov models. Simulation based MCMC maximum likelihood estimation techniques have been developed to replace the pseudolikelihood method. To date most work on ERGMs has focused on one-mode networks, with little done in the case of affiliation networks with two or more types of nodes. This paper proposes ERGMs for two-mode affiliation networks drawing on the recent advances for one-mode networks, including new two-mode specifications. We investigate features of the models by simulation, and compared the goodness of fit results obtained using the maximum likelihood and pseudolikelihood approaches. We introduce a new approach to goodness of fit for network models, using a heuristic based on Mahalanobis distance. The classic Southern Women data and Australian Interlocking Director data are used as examples to show that the ERGM with the newly specified statistics is a powerful tool for statistical analysis of affiliation networks.

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.

Basic notions for the analysis of large two-mode networks

Many large real-world networks actually have a two-mode nature: their nodes may be separated into two classes, the links being between nodes of different classes only. Despite this, and despite the fact that many ad hoc tools have been designed for the study of special cases, very few exist to analyse (describe, extract relevant information) such networks in a systematic way. We propose here an extension of the most basic notions used nowadays to analyse large one-mode networks (the classical case) to the two-mode case. To achieve this, we introduce a set of simple statistics, which we discuss by comparing their values on a representative set of real-world networks and on their random versions. This makes it possible to evaluate their relevance in capturing properties of interest in two-mode networks.

Connectance of Brazilian social bee: food plant networks is influenced by habitat, but not by latitude, altitude or network size

Several recent studies suggest that the level of generalization (measured as percentage connectance) of plant-pollinator networks has several ecological correlates, e.g. latitude and altitude. Here we report on levels of generalization in 27 two-mode networks of social bees and their food plants in various Brazilian habitats and urban environments. Social bees are generalist foragers and are among the most abundant flower visitors in Brazil. They probably account for 30-50% of all plant - flower visitor interactions. Connectance was significantly influenced by habitat. Cerrado forests showed lower connectance than the dry dune habitats, with Atlantic rain forest and urban sites taking intermediate position and arid Caatinga being similar to dunes. This shows that generalization in a plant - flower visitor community can be influenced by habitat even within a group of generalist flower visitors, in our case social bees. We show that the strength of the interactions is not different between Cerrado and semi-arid habitats (dunes and Caatinga) and discuss other explanations for our findings.