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.

A Tabu-Search Heuristic for Deterministic Two-Mode Blockmodeling of Binary Network Matrices.

Two-mode binary data matrices arise in a variety of social network contexts, such as the attendance or non-attendance of individuals at events, the participation or lack of participation of groups in projects, and the votes of judges on cases. A popular method for analyzing such data is two-mode blockmodeling based on structural equivalence, where the goal is to identify partitions for the row and column objects such that the clusters of the row and column objects form blocks that are either complete (all 1s) or null (all 0s) to the greatest extent possible. Multiple restarts of an object relocation heuristic that seeks to minimize the number of inconsistencies (i.e., 1s in null blocks and 0s in complete blocks) with ideal block structure is the predominant approach for tackling this problem. As an alternative, we propose a fast and effective implementation of tabu search. Computational comparisons across a set of 48 large network matrices revealed that the new tabu-search heuristic always provided objective function values that were better than those of the relocation heuristic when the two methods were constrained to the same amount of computation time.

Deterministic blockmodelling of signed and two-mode networks: A tutorial with software and psychological examples.

Deterministic blockmodelling is a well-established clustering method for both exploratory and confirmatory social network analysis seeking partitions of a set of actors so that actors within each cluster are similar with respect to their patterns of ties to other actors (or, in some cases, other objects when considering two-mode networks). Even though some of the historical foundations for certain types of blockmodelling stem from the psychological literature, applications of deterministic blockmodelling in psychological research are relatively rare. This scarcity is potentially attributable to three factors: a general unfamiliarity with relevant blockmodelling methods and applications; a lack of awareness of the value of partitioning network data for understanding group structures and processes; and the unavailability of such methods on software platforms familiar to most psychological researchers. To tackle the first two items, we provide a tutorial presenting a general framework for blockmodelling and describe two of the most important types of deterministic blockmodelling applications relevant to psychological research: structural balance partitioning and two-mode partitioning based on structural equivalence. To address the third problem, we developed a suite of software programs that are available as both Fortran executable files and compiled Fortran dynamic-link libraries that can be implemented in the R software system. We demonstrate these software programs using networks from the literature.

Intermediary organisations in collaborative environmental governance: evidence of the EU-funded LIFE sub-programme for the environment (LIFE-ENV).

In the framework of the collaborative environmental governance and specifically of network concepts, this study makes an exploratory analysis of the EU-funded LIFE sub-programme for the Environment (LIFE-ENV) and its priority area Environment and Resource Efficiency focused on the role of networks and in particular of intermediary organizations by using Social Network Analysis (SNA). More specifically, by investigating the evolving pattern of key statistics (density, clustering coefficient, betweenness and degree centrality) related to bipartite (organisations and projects) and dynamic (eleven years) networks, we identified 3003 organisations and 1006 projects and studied how they operate by forming new relations and reorganising existing connections. Results evidence that the LIFE-ENV attests a structural coherence and a stable structure over time and it is characterised by four different structures of network components, namely isolated coordinating beneficiary, isolated components, small components and giant components. Moreover, the LIFE-ENV is not a cohesive network, due to low values of both density and clustering coefficient. Based on betweenness centrality and degree centrality measures, the LIFE-ENV sub-programme has facilitated the emergence of 4855 intermediary organisations, which equals 29.5% of the total number of coordinating and associate beneficiaries involved in the programme in the eleven years considered. Transnational cooperation in the LIFE-ENV sub-programme is characterised by a different intensity of relations: some countries (i.e. Italy, Spain and Belgium) implement transnational cooperation with multiple European countries in both the North and South of Europe, while others tend to cluster with countries in the same geographical area, and lastly East European countries have limited participation in transnational cooperation. Our analysis supports the hypothesis of a declining collective action in the LIFE-ENV sub-programme.

A Social Relations and Networks Perspective of Depressive Symptoms in Older African Americans Relative to Two Other Ethno-racial Groups.

BACKGROUND AND OBJECTIVES: Family ties and role relationships through their effects on exchanges of resources and social support are critical health contexts for older African Americans. We studied the influence of affect-based (positive or negative) social relations and respondent-role network centrality on depressive symptoms in older African Americans compared to two ethno-racial groups, Black Caribbeans and Non-Hispanic Whites. RESEARCH DESIGN AND METHODS: We used data from the multigenerational 2004 National Survey of American Life Family Connections across Generations and Nations Study (NSAL 3-Gen). For respondents aged 50 years or older, we used tie affect (positive or negative) to code family role relations and two-mode (where an entity or thing is connected to a different type of entity, here individuals are connected to role relations) family networks. We used survey linear regressions to probe the independent association of relations and networks on depressive symptoms among older African Americans as compared to Black Caribbeans and Non-Hispanic Whites. RESULTS: Negative and positive relations are significantly associated with depressive symptoms, but there were some ethno-racial differences. For example, the negative Father relation is significantly associated with greater depressive symptoms among African Americans, but not in Black Caribbeans and Non-Hispanic Whites. Negative two-mode networks (connections from individuals to role relations) are significantly associated with depressive symptoms among African Americans and in the two comparison ethno-racial groups, while there is no significant association between positive networks and depressive symptoms. DISCUSSION AND IMPLICATIONS: We found that negative relations had larger effects on depressive symptoms than positive ones, and conversely that negative networks had larger effects than positive networks. Simultaneously modeling social relations and networks could potentially enhance our understanding of the links between social structure, and depressive symptoms among older adults in African American and other ethno-racial minorities.