Does candidate gender matter for vote choice? Whereas experimental research suggests an average preference for female candidates, observational studies tend to find null effects. In this note, we address the recent debate on how to measure voter preferences on the aggregate and the individual level. We argue that candidate gender preferences exist, but that whether and when they are revealed varies between and within voters. Drawing on an observational design and using data from over 500,000 individual ballots in Lithuanian elections, we employ multilevel regression and exponential random graph models to show how voters' candidate gender preferences are distributed across the electorate and how they vary in size and direction. We find that about half of all voters prefer either male or female candidates. Whereas preference for male candidates tends to be revealed in the first and second preference votes, preference for female candidates is first revealed in lower preference votes. Our results help explain contradictory findings in the literature and illustrate how observational data and methods can be used to assess voter preferences within electorates.

A rather unique feature of global climate negotiations is that most governments allow representatives of civil society organisations to be part of their national delegation. It remains unclear, however, why states grant such access in the first place. While there are likely to be benefits from formally including civil society, there are also substantial costs stemming from constraints on sovereignty. In light of this tradeoff, this article argues for a ‘contagion’ effect that explains this phenomenon besides domestic determinants. In particular, states, which are more central to the broader network of global governance, are more likely to be informed of and influenced by other states' actions and policies toward civil society. In turn, more central governments are likely to include civil society actors if other governments do so as well. This argument is tested with data on the participation of civil society organisations in national delegations to global climate negotiations between 1995 and 2005. To further uncover the underlying mechanisms, the article also provides an analysis of survey data collected at the United Nations Framework Convention on Climate Change (UNFCCC) negotiations in Durban in 2011.

In 2005, the European Parliament rejected the directive ‘on the patentability of computer‐implemented inventions’, which had been drafted and supported by the European Commission, the Council and well‐organised industrial interests, with an overwhelming majority. In this unusual case, a coalition of opponents of software patents prevailed over a strong industry‐led coalition. In this article, an explanation is developed based on political discourse showing that two stable and distinct discourse coalitions can be identified and measured over time. The apparently weak coalition of software patent opponents shows typical properties of a hegemonic discourse coalition. It presents itself as being more coherent, employs a better‐integrated set of frames and dominates key economic arguments, while the proponents of software patents are not as well‐organised. This configuration of the discourse gave leeway for an alternative course of political action by the European Parliament. The notion of discourse coalitions and related structural features of the discourse are operationalised by drawing on social network analysis. More specifically, discourse network analysis is introduced as a new methodology for the study of policy debates. The approach is capable of measuring empirical discourses both statically and in a longitudinal way, and is compatible with the policy network approach.

This article illustrates how qualitative and network evidence complement one another for obtaining a deeper understanding of meso-level social orders theorized as strategic action fields. Making use of network data based on Twitter follower relationships and building on a previous qualitative study on the food charities active in Greater Manchester, we show how network-analytic formalizations of even apparently unimportant digital connections—Twitter ‘follows’—can provide meaningful insights into the functioning of strategic action fields. Focusing on this local charitable food provision field, the article makes a number of broader empirical and methodological contributions potentially relevant to the study of non-profits and other multi-organizational fields. The results of the network analyses mostly confirm the findings obtained using qualitative data, but also point to potential contradictions and puzzles that may indicate further lines of inquiry. In the discussion, we highlight the strengths and limitations of this approach and suggest how researchers could use easily available digital network data at different phases of their field investigations.

In times of multiple crises and a looming partial breakup of the European Union, the question of what binds Europeans together appears more relevant than ever. This article proposes transnational attachment as a novel indicator of sense of community in Europe, arguing that this hitherto neglected dimension is substantially and structurally different from alternative ones such as cross‐border trust and identification. Combining Eurobarometer 73.3 data on ties between all EU‐27 countries with further dyadic data, it is shown empirically that the European network of transnational attachment has an asymmetric core‐periphery structure centred on five extremely popular countries (the United Kingdom, France, Germany, Italy and Spain). In line with transactionalist theory, cross‐border mobility and communication are strongly related to transnational attachment. Furthermore, the article demonstrates that the network of transnational attachment is much denser among those with a higher level of education than among those with a lower level. The results suggest that offering European citizens incentives to travel to peripheral countries may help counterbalance the current asymmetric structure of transnational attachment, thereby increasing Europe's social cohesion.

Celebrity philanthropy is a recent but widespread phenomenon in China. Using social network analysis, this paper seeks to answer the following questions: Is a celebrity’s position within a social network related to that celebrity’s philanthropic engagement, and how? Does a celebrity’s network position interact with normative influence to affect philanthropic engagement? What implications the study has for the development of modern philanthropy in China? Hypotheses regarding the associations between philanthropic engagement and a celebrity’s social network were tested using a sample from the “Celebrity Relationship Database.” Findings suggest that philanthropic engagement was more common in the center of the social network; under normative influence, a celebrity was more likely to engage in philanthropic activities if other members within the social network were active in philanthropic engagement; and, the effect of normative influence was stronger for celebrities who were positioned at the center of a social network than those who were positioned at the periphery. Implications for the development of modern philanthropy in China are also discussed.

Disaster usually provides a good opportunity to observe the convergence of voluntary organized response efforts. However, the extent to which response organizations and affected neighborhoods go through the relief process similarly or differently is surprisingly less studied. Integrating the framework of community ecology and the concept of community resilience, this study examines the evolutionary process of an emergent disaster response community that consists of the populations of response organizations and affected neighborhoods. Using a technological disaster that occurred in Taiwan in July 2014 as the research context, this study shows that response organizations’ resource provision network and affected neighborhoods’ resource receipt network exhibited similar structural tendencies over the phases of disaster response and rebuilding. The process of mutual resource mobilization was also observed as response organizations mobilized and provided resources to affected neighborhoods at the same time. Moreover, while affected neighborhoods tended to maintain their resource relationships consistently over time, the changing structural patterns of their resource network reflected individual engagement in resuming normality after the incident. Theoretical and practical implications for emergent post-disaster social and voluntary behavior are discussed through the lens of community ecology and community resilience.

While a rich literature investigates how and why NPOs use social media, research on why they differ in their social media adoption (SMA) is limited. In this paper we examine how NPOs’ interorganizational partner portfolio characteristics can enable or constrain their adoption of social media, including blogs and videos, conventional social media (Facebook, Twitter…) and crowd-based platforms (crowdfunding and petitions). Based on a survey distributed to a sample of environmental NPOs in France, results indicate that NPOs having open networks, whose partners are physically distant, and that have more cross-sectoral partners have higher SMA. Network portfolio management can thus make up for a shortage of financial resources to invest in social media.

Collaborative governance among multiple stakeholders is typically essential for conserving complex social-ecological systems. Mexico’s ‘biocultural landscapes’ – a territorial governance initiative – may be seen as pioneering models to promote this. However, actual outcomes depend on the initial conditions, institutional design, leadership and details of the collaborative process. We used a mixed-methods approach combining social network analysis and semi-structured interviews to analyse the structure of the collaboration network within Mexico’s Sierra Occidental Biocultural Landscape (SOBL). Our findings revealed a sparse, low-reciprocity network dominated by a few public managers, indicating potential power imbalances and challenges to building trust. Stakeholder interviews showed misalignments with theoretical collaborative governance including power imbalances, limited inclusiveness and a lack of trust among participants. While the SOBL has achieved collaborative results, such as the community forest fire brigades and the development of land management plans, achieving its full potential as a model for biocultural conservation requires addressing power dynamics and building a more equitable governance structure.

Why does collaboration among competitors persist as industries mature? Standard models predict it will fade with formal governance and rivalry, yet in some sectors, it becomes a stable norm. Using a Veblenian Original Institutional Economics (OIE) lens, this paper develops a four-stage heuristic linking evolving uncertainty (radical, relational, coordination, durability) to distinct coordination logics. A mixed-methods study of the U.S. artisanal cheese industry (1975–2018) shows that collaboration became institutionalised through habituated practice, identity alignment, and moral commitment, later layered with formal supports. The framework clarifies how OIE best explains norm emergence and reproduction, while New Institutional Economics (NIE) helps account for codifying and scaling already-institutionalised norms. Quantitatively, peer networks shifted toward higher clustering and greater geographic localisation; qualitatively, mentorship and open exchange sedimented into professional expectations. Collaboration endures because it is morally meaningful, identity-affirming, and institutionally reproduced. Efficiency benefits may follow, but they do not explain its origin or persistence.

This article investigates the organization of a transnational criminal enterprise through a detailed case study of Operation Singapore, a network producing and trafficking falsified pharmaceuticals from China to the United Kingdom. Drawing on law enforcement records, court transcripts, digital communications, and expert interviews, the study maps the structure and strategies of this criminal enterprise. It applies Peter Reuter’s theory of criminal organization, and Niles Breuer and Federico Varese’s typology of network forms to show how functional roles shape organizational structure: production was hierarchical and security-driven, while distribution was decentralized and transactional. Trust was not based on kinship or ethnicity but constructed through moral appeals and restricted information flows. The case reveals how criminal actors exploit legal frameworks and commercial infrastructures to mask illegal activity and blur boundaries between legal and illegal markets. These findings challenge static models of organized crime and call for a more dynamic, relational understanding of criminal enterprise.

This study examines gender bias in the investigative work of medieval inquisitors, focusing on Albert of Castellario’s trial of the Waldensians in Giaveno, Italy, in 1335. Drawing upon advancements in sociological and criminological literature, we conceptualize an inquisitorial trial as a discretionary information-gathering endeavor contingent upon the inquisitor’s judgment in deciding which leads to pursue. Employing social network analysis and survival methods, we evaluate whether Albert demonstrated gender biases in his investigative decisions, particularly regarding the weight assigned to testimonies from men versus women. Our findings demonstrate that Albert was more inclined to investigate men and prioritize their testimonies, even where similar levels of incriminating evidence were present for both genders. These results highlight the influence of societal attitudes toward gender on inquisitorial practices, on the representativeness of historical records, and on prevailing understandings of heretical groups. Furthermore, this study underscores the broader utility of our methodological framework for addressing related historical inquiries, including the political motivations behind the medieval inquisition.

Positive health outcomes are realized when individuals receive interprofessional care, which also includes collaboration with family and care providers. We used social network analysis to explore interprofessional care networks and experiences of independent, community-dwelling older adults and how they perceive collaboration between different medical and non-medical network members. Twenty-three participants were interviewed and asked to name individuals contributing to their health and well-being (network of care) and position them in a concentric circle to reflect the relative strength of relationships. The average network size was 11. Closest relationships were with spouses, children, and family physicians. Relationship strength with network members was marked by frequency, accessibility, longevity, and impact of interactions. Participants were ardent self-advocates for their care, but reported few apparent episodes of collaboration between network members. Our study highlights that coordinated and collaborative care for independent community-dwelling older adults is lacking and does not routinely engage non-medical network members.

A priority of the Northern New England Clinical and Translational Research (NNE-CTR) Network is conducting, promoting, and advancing community-engaged research through its Community Engagement and Outreach (CEO) Core. We sought to measure the CEO Core’s success in strengthening community-level research partnerships using a validated survey platform based on network science to map and track collaborations over time. The survey was completed by 59/76 organizations (77.6% response rate). Key findings included a high level of trust and a modest level of perceived value relative to published benchmarks. Additional specific findings will inform opportunities to improve the network as the NNE-CTR matures.

This article investigates geosocial patterns of marriage strategies among the leadership of Hasidism, arguably the most prominent socio-religious movement of modern Jewry, known for its unique network of charismatic leaders organized in hereditary dynasties. The article’s core premise is that grasping the network structure of the Hasidic movement’s dynasties, which has been under-researched, is crucial to understanding the movement’s social and cultural dynamics. The study employs social network analysis (SNA) and spatial analysis to examine marital unions among these leaders (2,375 cases), from the early stages of the movement in the eighteenth century until the early twenty-first century. The article explains, for the first time, how Hasidic dynasties expanded, eroded, and negotiated their status within the network of other dynasties. More specifically, we analyze the position of the dynasties within a wider context of social and spatial interconnection patterns, the significance of endogamy, the impact of territorial factors on marriage preferences, and the creation of dynastic clusters. A significant conclusion of this article is that, rather than a set of unrelated dynasties, Hasidic leadership gradually became a web of interconnected families with explicable patterns of organization. These findings can help explain historical processes in Hasidism, such as its persistence through historical crises. It can also illuminate leadership processes in other religions in which, as in Hasidism, the social structure of charismatic leadership is based on clans.

One difficulty in studying “astronomers” and “mathematicians” as distinct classes in ancient China is that the important ones were neither specialists nor professionals, but polymaths, with little to distinguish them from any other intellectual. Another difficulty, confounding any modern taxonomy, is the tight relationship between astronomy, mathematics, Classical exegesis, and ritual. This article uses the thousands of lost and extant works cataloged under discrete emic categories in the Hanshu, Suishu, and Jiu Tangshu bibliographic treatises to weigh the place of the sciences and their practitioners vis-à-vis other contemporary forms of knowledge and, using polymathy as a vector, to map the connectivity and clusters between fields. It presents numerous findings about relative anonymity, fame, productivity, and the fields in which “scientists” were most implicated, but its principal interest is in proposing a method to sidestep modern observer’s categories.

A social network comprises both actors and the social connections among them. Such connections reflect the dependence among social actors, which is essential for individuals’ mental health and social development. In this article, we propose a mediation model with a social network as a mediator to investigate the potential mediation role of a social network. In the model, the dependence among actors is accounted for by a few mutually orthogonal latent dimensions which form a social space. The individuals’ positions in such a latent social space are directly involved in the mediation process between an independent and dependent variable. After showing that all the latent dimensions are equivalent in terms of their relationship to the social network and the meaning of each dimension is arbitrary, we propose to measure the whole mediation effect of a network. Although individuals’ positions in the latent space are not unique, we rigorously articulate that the proposed network mediation effect is still well defined. We use a Bayesian estimation method to estimate the model and evaluate its performance through an extensive simulation study under representative conditions. The usefulness of the network mediation model is demonstrated through an application to a college friendship network.

Spanning nearly sixty years of research, statistical network analysis has passed through (at least) two generations of researchers and models. Beginning in the late 1930's, the first generation of research dealt with the distribution of various network statistics, under a variety of null models. The second generation, beginning in the 1970's and continuing into the 1980's, concerned models, usually for probabilities of relational ties among very small subsets of actors, in which various simple substantive tendencies were parameterized. Much of this research, most of which utilized log linear models, first appeared in applied statistics publications.

But recent developments in social network analysis promise to bring us into a third generation. The Markov random graphs of Frank and Strauss (1986) and especially the estimation strategy for these models developed by Strauss and Ikeda (1990; described in brief in Strauss, 1992), are very recent and promising contributions to this field. Here we describe a large class of models that can be used to investigate structure in social networks. These models include several generalizations of stochastic blockmodels, as well as models parameterizing global tendencies towards clustering and centralization, and individual differences in such tendencies. Approximate model fits are obtained using Strauss and Ikeda's (1990) estimation strategy.

In this paper we describe and extend these models and demonstrate how they can be used to address a variety of substantive questions about structure in social networks.