This study develops a principal–agent theory of why armed groups engage in high-end cooperation involving training or intelligence. While such cooperation enhances capacity, it generates downstream risks. Principals mitigate these risks by selecting agents who are skill-wise complementary but politically non-substitutable. Agents accept high-end support when doing so does not leave them politically overshadowed by a dominant actor. Using original network data on 53 groups in Northeast India (1981–2021) and temporal exponential random graph models, I show that high-end cooperation is more likely in dyads characterized by organizational capacity differentials, complementary attack portfolios, and distinct constituencies. The findings recast militant alliances as products of competitive threat perception and carry broader implications for the study of multiparty conflicts.

Research on individual differences in social network analysis has primarily focused on how personality traits influence individuals’ positions and behaviors within social structures. However, attachment research has consistently shown that attachment styles strongly affect how people form and maintain their interpersonal relationships. This study examined how attachment styles relate to different types of individual personal networks. A classification of personal networks was developed based on structural indicators of cohesion, transitivity, and subgroup configuration, among other measures. Density, fragmentation, and centralization emerged as the most discriminant metrics for clustering solutions. Results indicated that attachment styles have greater explanatory power than the Big Five model in accounting for distinct relational configurations. Specifically, secure attachment was associated with dense, noncentralized, and supportive personal networks, whereas avoidant attachment and openness to experience were linked to fragmented, modular, and less supportive networks. Sociodemographic variables showed the highest predictive value for the type of personal network.

This article examines the renewal of Spain's corporate elite between 1920 and 2020 by combining Social Network Analysis with prosopography. Using interlocking directorate data for the two hundred largest Spanish firms, aggregated into three periods (1920–1950, 1960–1980, and 1990–2020), the study identifies the most structurally central directors and reconstructs their social origins, education, and career trajectories. The findings reveal that while the structural core of corporate power remained remarkably stable—between thirty-four and forty individuals per period, less than 1 percent of all directors—its social composition changed substantially. Aristocratic backgrounds and dynastic ties gave way to middle-class origins, public university credentials, and senior civil service careers. Two institutional channels drove this transformation: the state, whose role shifted from direct political overlap to technocratic circulation through public administration; and the public university system, which increasingly replaced inherited status as the basis of elite recruitment. Rather than democratization, renewal took the form of controlled circulation: new actors entered through selective pathways while the underlying power structure remained intact. By adopting an interpersonal perspective over a full century, the article addresses a persistent gap in the literature on interlocking directorates, which has focused mainly on firm-centered networks rather than their most central actors.

Ethical considerations in social network studies are grounded in the general principles of human subjects’ research, including avoidance of harm, promotion of justice, equitable distribution of burdens and benefits, respect for human dignity, and protection of confidentiality. To help navigate these challenges, this article presents recommendations for conducting ethical network research, developed by a multi-disciplinary and multi-national working group. The article is divided in three main sections where there are certain recommendations identified for each one of them: data collections, use, and availability. Discovering how others addressed and solved problems can be a way for all of us to improve our capacity to stand up to the scrutiny of ethical governance bodies, while also increasing our capacity to responsibly address novel, rare, or otherwise difficult situations for which institutions provide limited guidance. We see this as a first step toward a virtuous circle, or a form of “generalized indirect reciprocity” whereby researchers share information that may be relevant for others, and benefit at the same time from the information given by other members of the social networks analysis community. Our goal is to continue to produce and promote scientifically solid, ethical social network research.

Twitter is one of the most widely used social networks globally but is also notorious for harbouring significant levels of hate speech. This paradox has garnered the attention of companies and governments concerned about how digital hate can fragment communities and incite real-world violence. While extensive research has focused on detecting hate speech, there is a lack of comprehensive analysis of the actors involved, their characteristics, and their interactions within the online environment. Common assumptions categorise users into merely two groups—haters and non-haters—overlooking the existence of other groups that may more accurately represent the dynamics of hate dissemination. Additionally, existing user classification models often rely on large volumes of tweet data, a limitation given the restricted access to the Twitter API. Social networks are also frequently visualised using graphs where edges represent only superficial relationships. This study addresses these gaps through five research questions. We propose formal user clustering methods and develop a classifier that uses exclusively profile attributes—information more readily obtainable from the network. We also introduce a more nuanced definition of interaction for graph edges, based on ideological support or opposition between users. To conduct our analysis, we have extracted two complementary datasets: (i) a keyword-based corpus of 3.3M Spanish tweets containing hate-associated terms, of which 1.6M unique tweets were retained after filtering and (ii) a user-based corpus comprising timelines of $\approx$3,000 users linked to hate speech, totalling over 3 M tweets. Our results reveal the existence of three primary user classes—haters, upstanders, and neutrals—in contrast to the conventional binary classification. We demonstrate that profile attributes are reliable indicators for automatically classifying users and find significant statistical differences between these classes. Finally, we develop a graph visualisation tool to assist authorities in analysing interactions among different user types, providing a useful exploratory tool to support the analysis of online hate and inform potential mitigation strategies.

Historical and criminological studies of female participation in gangs and organized crime have tended to focus on mixed-sex, male-dominated groups. This article offers an examination of the “Forty Elephants” gang, an all-female criminal group that operated in twentieth-century Britain. Drawing on digitized newspaper sources, the study uses social network analysis (SNA) to trace structural shifts across two periods associated with different leaders of the gang. The findings reveal a shift from a relatively centralized network in the gang’s earlier years to a looser, more diffuse structure in the later period, with influence spread across multiple figures rather than concentrated in a single, dominant leader. These structural changes are contextualized within broader historical developments, including internal gang conflict, law enforcement attention, criminal justice responses, and shifts in offending methods. By combining quantitative SNA with qualitative historical analysis, the article demonstrates how digital methods can reveal overlooked patterns of female collaboration and co-offending. In doing so, it challenges stereotypes of women as marginal offenders and provides a methodological model for applying network analysis to historical crime research, where such methods remain underused.

This study examines the Advancing Conservation through Empathy for Wildlife™ (ACE for Wildlife™) Network, a collaborative professional network that draws on elements of the collective impact model to foster empathy for wildlife and advance conservation goals. Using a mixed-methods case study design, including social network analysis and qualitative interviews, we examine how the Network’s structured design and facilitation supported information-sharing and collaboration among participating zoos and aquariums. The results demonstrate that information-sharing served as a critical foundation for collaboration, with participants forming new partnerships and leveraging shared resources. The study highlights the roles of centralized backbone coordination and bridging individuals in supporting network connectivity, shared learning and collaboration. We provide insights into how intentionally designed professional networks can strengthen practice within the zoo and aquarium field and contribute to understanding how collaboration can be supported in other sectors working towards shared environmental or learning goals.

Relationships among teachers are known to influence their teaching-related perceptions. We study whether and how teachers’ advising relationships (networks) are related to their perceptions of satisfaction, students, and influence over educational policies, recorded as their responses to a questionnaire (item responses). We propose a novel joint model of network and item responses (JNIRM) with correlated latent variables to understand these co-varying ties. This methodology allows the analyst to test and interpret the dependence between a network and item responses. Using the JNIRM, we discover that teachers’ advising relationships contribute to their perceptions of satisfaction and students more often than their perceptions of influence over educational policies. In addition, we observe that the complementarity principle applies in certain schools, where teachers tend to seek advice from those who are different from them. The JNIRM has the potential to improve the cost efficiency of network studies by integrating network and item response information during model estimation.

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.