Understanding the values held by negotiating parties is central to the design and success of international climate change agreements. However, empirical understandings of these values – and the manners by which they structure negotiating countries’ value networks and interactions over time – are severely limited. In addressing this shortcoming, this paper uses keyword-assisted topic models to extract value networks for the 13 most recent Conferences of the Parties (COPs) to the United Nations Framework Convention on Climate Change (UNFCCC). It then uses network analysis tools to unpack these networks in relation to influential values, countries, and time. In doing so, it demonstrates that countries’ core climate change values (i) can be accurately recovered from COP High-level Segment (HLS) speeches and (ii) can, in turn, be used to understand the structure of negotiation networks at the UNFCCC. Analysis of the corresponding value networks for COPs 16–28 indicates that initially central values of “Fairness” and “Power” have increasingly given way to values associated with the “Environment” and “Achievement.” Thus, countries at the UNFCCC have increasingly eschewed values associated with common but differentiated responsibilities in favor of a consensus over the urgency of collectively combating climate change. These and related insights illustrate our approach’s potential for recovering and understanding value networks within climate change negotiations – a critical first step for any successful climate change agreement.

Previous research has identified intermarriage as an important factor in immigrant integration, but what affects immigrants’ willingness to intermarry or support intermarriage? A significant and understudied aspect of attitudes toward intermarriage among immigrants is the role of religion. We focus on a particular group of immigrants, Bhutanese refugees, for whom religious persecution featured prominently in their forced migration and resettlement in the US. Using an individual-level survey, we explore factors affecting their attitudes toward intermarriage. Specifically, we analyze the impact of social interactions, socioeconomic conditions, and demographic factors on resettled Bhutanese refugees’ attitudes toward intermarriage. Results indicate that, in addition to age, income, and English proficiency, resettled refugees who spend more time interacting with individuals from outside of their own ethnic, cultural, and religious group are more likely to support intermarriage. Social interactions may allow refugees to overcome religious restrictions and advance refugee integration into American society through intermarriage.

The Latent Position Model (LPM) is a popular approach for the statistical analysis of network data. A central aspect of this model is that it assigns nodes to random positions in a latent space, such that the probability of an interaction between each pair of individuals or nodes is determined by their distance in this latent space. A key feature of this model is that it allows one to visualize nuanced structures via the latent space representation. The LPM can be further extended to the Latent Position Cluster Model (LPCM), to accommodate the clustering of nodes by assuming that the latent positions are distributed following a finite mixture distribution. In this paper, we extend the LPCM to accommodate missing network data and apply this to non-negative discrete weighted social networks. By treating missing data as “unusual” zero interactions, we propose a combination of the LPCM with the zero-inflated Poisson distribution. Statistical inference is based on a novel partially collapsed Markov chain Monte Carlo algorithm, where a Mixture-of-Finite-Mixtures (MFM) model is adopted to automatically determine the number of clusters and optimal group partitioning. Our algorithm features a truncated absorb-eject move, which is a novel adaptation of an idea commonly used in collapsed samplers, within the context of MFMs. Another aspect of our work is that we illustrate our results on 3-dimensional latent spaces, maintaining clear visualizations while achieving more flexibility than 2-dimensional models. The performance of this approach is illustrated via three carefully designed simulation studies, as well as four different publicly available real networks, where some interesting new perspectives are uncovered.

Focusing on gender inequality in a local community elite, we investigate the role of gender in access to and participation in networks of nonprofit trustees in Louisville, Kentucky. We examine two types of network relations: participation in the network of overlapping board memberships (the “structural network”) and interpersonal ties of collegiality and friendship (the “social network”). Asking whether the gender hierarchy found in most private and public sector organizations is mirrored in this inner circle of trustees, with men occupying the most influential positions in the structural and social networks, we find some male advantage in the structural network. Men predominate in holding most board seats, occupying multiple board seats, and in having slightly greater network centrality. By contrast, women hold the edge in the social network, with slightly greater centrality and higher levels of social integration. Women’s disadvantage in the structural network is at least partly counterbalanced by their prominence in the social network of trustees in Louisville. Results indicate that the local nonprofit sector includes a small number of women (but no people of color) in leadership roles.

This paper argues that the operating environment of humanitarian assistance is best conceived as an interorganizational social network or regime and that the problem of power and authority in such situations must be re-founded or reconceived accordingly. This contention is developed to contribute to an important ongoing dialogue among analysts concerning how humanitarian aid may most effectively be delivered in the context of a realistic appraisal of the structural and operating conditions in which it is offered. The paper first outlines the primary elements of the organizational environment in which humanitarian efforts must proceed, next suggests a way of thinking about how one might conceive of those conditions that builds on recent work, and then sketches the elements of a strategic contingency approach to the humanitarian assistance coordination dilemma. This analytical frame leads one to rethink assumptions concerning how best to conceptualize both the environment and the behavior of humanitarian organizations engaged in providing assistance in emergency situations and to suggest that theory building for this domain of study should now turn to a network-based and strategically contingent perspective for its foundation.

The civil society organizations networks in the Latin American region are increasingly participating in the public policy advocacy. There are many studies that address them, but they do it through more in qualitative methodological approaches but there are few analyzed from a social network analysis approach. We present a case study that analyzes the American Network for Intervention in Situations of Social Suffering (Red Americana de Intervención en Situaciones de Sufrimiento Social, RAISSS), a transnational network of civil society networks from 15 Latin American countries that work with the same meta-model, called ECO2, to promote social inclusion and public policy advocacy.

Participation in voluntary associations is an important part of an immigrant’s integration into a host country. This study examines factors that predispose an immigrant’s voluntary involvement in religious and secular organizations compared to non-immigrants (“natives”) in Canada, and how immigrants differ from natives in their voluntary participation. The study results indicate that informal social networks, religious attendance, and level of education positively correlate with the propensity of both immigrants and natives to participate and volunteer in religious and secular organizations. Immigrants who have diverse bridging social networks, speak French and/or English at home, and either attend school or are retired are more likely to participate and volunteer for secular organizations. Further, social trust matters to native Canadians in their decision to engage in religious and secular organizations but not to immigrants. Pride and a sense of belonging, marital status, and the number of children increase the likelihood of secular voluntary participation of natives but not of immigrants. These findings extend the current understanding of immigrant integration and have important implications for volunteer recruitment.

Using data from the 2008 General Social Survey of Canada, this study examines the factors associated with individuals’ propensity to engage in formal and informal volunteering. The results show that social networks increase the likelihood of both formal and informal volunteering, but social trust and human capital increase only the likelihood of formal volunteering and not of informal care. The findings also reveal interesting cultural influences and regional differences in the propensity to engage in formal and informal volunteering, especially between French-speaking Canadians and English-speaking Canadians, and those living in Quebec and outside of Quebec. Native-born Canadians are more likely to volunteer than their immigrant counterparts, but they are similar to immigrants in the propensity to provide informal care. Additionally, women are found to be more likely to engage in formal volunteering and informal care than men. Theoretical and practical implications of the findings are discussed.

This study focuses on the role of individuals’ social networks and motivations in predicting their intention to participate socially. In an online survey, university students (N = 263) estimated the likelihood of their future participation in several types of civic and political activity and evaluated their possible motivations. Participants also indicated approximately how many of their social contacts were already involved in each type of participation, with this measure being used to calculate their degree centrality in social networks. Multiple linear regression analyses revealed that motivations and social contacts were significant predictors of intention to engage in most forms of civic and political activity studied. Social contacts were more decisive in predicting political than civic participation. We also found that personal motivations mediated the relationship between social contacts and intention to participate in all cases except joining a political party. We discuss the results in light of their theoretical and practical implications.

The main goal of this paper is to introduce a new model of evolvement of beliefs on networks. It generalizes the DeGroot model and describes the iterative process of establishing the consensus in isolated social networks in the case of nonlinear aggregation functions. Our main tools come from mean theory and graph theory. The case, when the root set of the network (influencers, news agencies, etc.) is ergodic is fully discussed. The other possibility, when the root contains more than one component, is partially discussed and it could be a motivation for further research.