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Since Oscar Schachter’s articulation of the concept, scholars have attempted to better understand the ‘invisible college of international lawyers’ making up our profession. They have done this through piecemeal surveys of public professional rosters (arbitrators, International Court of Justice counsel), piecing together anecdotes of connections between members, or constructing stories about individuals’ role in discrete legal developments. Departing from these approaches, we use the obituaries published in the British Yearbook of International Law (1920–2017) to draw an interactive map of the ‘invisible college’. Obituaries are a unique window into international law’s otherwise private inner life, unveiling professional and personal connections between international lawyers and their shared career paths beyond single institutions or individual stories. Employing network analysis, a method commonly used in social sciences to describe complex social phenomena such as this, we are able to demonstrate the ubiquity of informal networks whereby ideas move, and provide evidence of the community’s homogeneity. Exploring connections between international lawyers and their shared characteristics in this novel way, we shed light on the features of this group and the potential impact individual personalities have on the law. These characteristics of the profession and its members are evident to insiders but externally invisible. Graphic representation is a powerful tool in bolstering critiques for diversity and contestation of mainstream law-making narratives. Rather than exhaustively mapping, however, we propose to take the ‘dead white men’ trope to an extreme, provoking the reader to question the self-image of the profession as an impersonal expert science.
We develop a theoretical framework that accounts for complex dependence in foreign direct investment (FDI) relationships. Conventional theories of FDI focus on firm-, industry-, country-, or dyad-level characteristics to account for cross-border capital movements. Yet, today's globalized economy is characterized by the increasing fragmentation and dispersion of production processes, which gives rise to complex dependence among production relationships. Consequently, FDI flows should be represented and theorized as a network. Specifically, we argue that FDI relationships are reciprocal and transitive. We test these hypotheses along with conventional covariate determinants of FDI using an exponential random graph model (ERGM) for weighted networks. We find that FDI networks exhibit strong reciprocity and transitivity. Our network approach to studying FDI provides new insights into cross-border investment flows and their political and economic consequences, and more generally the dynamics of globalization. In addition to our substantive findings, we offer a broad methodological contribution by introducing the ERGM for count-weighted networks in political science.
Isolation is a concept originally conceived in the context of clique enumeration in static networks, mostly used to model communities that do not have much contact to the outside world. Herein, a clique is considered isolated if it has few edges connecting it to the rest of the graph. Motivated by recent work on enumerating cliques in temporal networks, we transform the isolation concept to the temporal setting. We discover that the addition of the time dimension leads to six distinct natural isolation concepts. Our main contribution is the development of parameterized enumeration algorithms for five of these six isolation types for clique enumeration, employing the parameter “degree of isolation.” In a nutshell, this means that the more isolated these cliques are, the faster we can find them. On the empirical side, we implemented and tested these algorithms on (temporal) social network data, obtaining encouraging results.
Poor connectivity between diverse resource users and complex wider governance networks is a challenge in environmental governance. Organizations that ‘broker’ interactions among these relationships are expected to improve governance outcomes. Here, we used semi-structured interviews and social network analysis to identify actors in positions to broker coral reef-related information to and from resource users and to assess the performance of these brokers. Representatives (n = 262) of actor groups were interviewed, including local and national government, non-governmental organizations (NGOs), community organizations and resource user groups from 12 communities across four Caribbean countries, to map information-sharing networks and to identify brokers. Broker performance was assessed through separate interviews with coral reef resource users (n = 545). The findings show that marine NGOs were the highest-functioning brokers. Where such local-level organizations were absent, government agencies in reef management roles acted as brokers, but their performance was lower. Actors in brokerage positions did not always effectively share information, with broker performance being positively correlated with network brokerage scores. The results further our understanding of the roles of brokers in different governance contexts. Identifying those in brokerage positions and supporting their roles in connecting local resource users to wider governance networks could encourage functional brokerage and enhance reef management outcomes.
We used social network analysis (SNA) to study the novel coronavirus (COVID-19) outbreak in Karnataka, India, and to assess the potential of SNA as a tool for outbreak monitoring and control. We analysed contact tracing data of 1147 COVID-19 positive cases (mean age 34.91 years, 61.99% aged 11–40, 742 males), anonymised and made public by the Karnataka government. Software tools, Cytoscape and Gephi, were used to create SNA graphics and determine network attributes of nodes (cases) and edges (directed links from source to target patients). Outdegree was 1–47 for 199 (17.35%) nodes, and betweenness, 0.5–87 for 89 (7.76%) nodes. Men had higher mean outdegree and women, higher mean betweenness. Delhi was the exogenous source of 17.44% cases. Bangalore city had the highest caseload in the state (229, 20%), but comparatively low cluster formation. Thirty-four (2.96%) ‘super-spreaders’ (outdegree ⩾ 5) caused 60% of the transmissions. Real-time social network visualisation can allow healthcare administrators to flag evolving hotspots and pinpoint key actors in transmission. Prioritising these areas and individuals for rigorous containment could help minimise resource outlay and potentially achieve a significant reduction in COVID-19 transmission.
Crisis management in major accidents requires the collaboration among different organizations. One of the most important problems of crisis management is the lack of coordination between executive organizations. The aim of this study was to examine the structural characters and problems of interorganizational network during crisis in the petrochemical industry and provide solutions to achieve the highest performance in crisis management.
The organizations involved in crisis management were identified through interviews and questionnaires. Gephi (0.9.1) software was used to examine interorganizational relationships.
In this study, the crisis management team consisted of 25 public and private organizations and non-governmental organizations. The highest betweenness centrality was observed in Crisis Management of Provincial Government (CMPG) (142.16) and Fire Department of Petrochemical Complex (FDC) (89.3). The highest closeness centrality was observed in FDC (0.77), CMPG (0.7), Shazand Governorate (0.7), and Crisis Management of University of Medical Sciences (0.7).
Coordination between organizations plays an important role in crisis and emergency management, and social network analysis helps identify strengths and weaknesses of organizations involved in crisis management, overcome those weaknesses, and consequently achieve the best performance in crisis management.
The purpose of this study was to demonstrate the use of social network analysis to understand public discourse on Twitter around the novel coronavirus disease 2019 (COVID-19) pandemic. We examined different network properties that might affect the successful dissemination by and adoption of public health messages from public health officials and health agencies.
We focused on conversations on Twitter during 3 key communication events from late January to early June of 2020. We used Netlytic, a Web-based software that collects publicly available data from social media sites such as Twitter.
We found that the network of conversations around COVID-19 is highly decentralized, fragmented, and loosely connected; these characteristics can hinder the successful dissemination of public health messages in a network. Competing conversations and misinformation can hamper risk communication efforts in a way that imperil public health.
Looking at basic metrics might create a misleading picture of the effectiveness of risk communication efforts on social media if not analyzed within the context of the larger network. Social network analysis of conversations on social media should be an integral part of how public health officials and agencies plan, monitor, and evaluate risk communication efforts.
In this chapter, we make an argument that reentry process and its outcome could be better represented, understood, and explained from a social network perspective. We first review the theories and empirical findings of previous research on reentry using social relations as the binding theme. We then introduce social network analysis and highlight its complementary role to conventional reentry studies. On such basis, an integrated social network theory of reentry is proposed and its various propositions presented. FInally, the implications of this theoretical framework for intercultural training are discussed in detail and suggestions for training design and evaluation are provided.
Community-based physical activity programs, such as the Recreovía, are effective in promoting healthy behaviors in Latin America. To understand Recreovías’ challenges and scalability, we characterized its social network longitudinally while studying its participants’ social cohesion and interactions. First, we constructed the Main network of the program’s Facebook profile in 2013 to determine the main stakeholders and communities of participants. Second, we studied the Temporal network growth of the Facebook profiles of three Recreovía locations from 2008 to 2016. We implemented a Time Windows in Networks algorithm to determine observation periods and a scaling model of cities’ growth to measure social cohesion over time. Our results show physical activity instructors as the main stakeholders (20.84% nodes of the network). As emerging cohesion, we found: (1) incremental growth of Facebook users (43–272 nodes), friendships (55–2565 edges), clustering coefficient (0.19–0.21), and density (0.04–0.07); (2) no preferential attachment behavior; and (3) a social cohesion super-linear growth with 1.73 new friendships per joined user. Our results underscore the physical activity instructors’ influence and the emergent cohesion in innovation periods as a co-benefit of the program. This analysis associates the social and healthy behavior dimensions of a program occurring in natural environments under a systemic approach.
Migration is often perceived as a challenge to the welfare state. To manage this challenge, advanced welfare states have established transgovernmental networks. This article examines how domestic factors condition the interaction of representatives of advanced welfare states when they cooperate on transnational welfare governance. Based on new survey data, it compares who interacts with whom in one of the oldest transgovernmental networks of the European Union (EU) – the network that deals with EU citizens' rights to cross-border welfare. First, the authors perform a welfare cluster analysis of EU-28 and test whether institutional similarity explains these interactions. Furthermore, they test whether the level and kind of migration explains interaction and examine the explanatory value of administrative capacity. To test what drives interactions, the study employs social network analysis and exponential random graph models. It finds that cooperation in networked welfare governance tends to be homophilous, and that political cleavages between sending and receiving member states are mirrored in network interactions. Domestic factors are key drivers when advanced welfare states interact.
This article investigates the relationship between director networks and earnings quality in Malaysia. Using data on 4,416 individual directors who served on the boards of 745 firms listed on Bursa, Malaysia during 2011, we map the entire network of directors and generate measures to reflect the size and quality of information within the network. We find a negative and significant relationship between the overall connectedness of a director's network and the firm's earnings quality. In addition, we find a negative and significant relationship between the political connectedness of the director's network and earnings quality. Our results are robust for different measures of earnings quality.
This article examines provincial policy influence on long-term care (LTC) professionals’ advice-seeking networks in Canada’s Maritime provinces. The effects of facility ownership, geography, and region-specific political landscapes on LTC best-practice dissemination are examined. We used sociometric statistics and network sociograms, calculated from surveys with 169 senior leaders in LTC facilities, to identify advice-seeking network structures and to select 11 follow-up interview participants. Network structures were distinguished by density, sub-group number, opinion leader, and boundary spanner distribution. Network structure was affected by ownership model in Nova Scotia and Prince Edward Island, and by regional geography in New Brunswick. Political instability within each province’s LTC system negatively affected network actors’ capabilities to enact innovation. Moreover, provincial policy variations influence advice-seeking network structures, facilitating and constraining relationship development and networking. Consequently, local policy context is essential to informing dissemination strategy design or implementation.
Organizations can expand their impact through strategic partnerships. We used social network analysis to compare two network theories in order to determine whether zoos’ conservation partnerships form networks that reflect collaborative social movements or business-style competition. Data from 234 zoos revealed a conservation network involving 1679 organizations with 3018 partnerships. The network had 40 subgroups: 1 large network, 6 small networks and 33 disconnected zoos. Social network analysis metrics revealed an incohesive and low-density network. Zoos are more likely to behave competitively like businesses with limited partnerships to protect resources, rather than behaving as collaborative social movement organizations partnering to further the cause of conservation across their communities. Content analyses of organizational activities revealed that 62% of zoos’ partners display different skills and roles in conservation projects, while 38% participated in the same activities as zoos. These novel findings about zoos behaving as competitive institutions inform opportunities for better collaboration in order to expand organizations’ conservation impact.
The Mount Sinai Health Hackathon is designed to provide a novel forum to foster experiential team science training. Utilizing a Social Network Analysis survey, we studied the impact of the Mount Sinai Health Hackathon on the nature of collaborative relationships of hackathon participants. After the event, the number of links between participants from different disciplines increased and network density overall increased, suggesting a more interconnected network with greater interdisciplinary communication. This social network approach may be a useful addition to the evaluation strategies for team science education initiatives.
This study examined the way organizations were involved in the response to the Middle East Respiratory Syndrome Coronavirus (MERS-CoV, MERS) outbreak that occurred in Korea in 2015.
Data and Methods:
We collected organizational network data through a content analysis of online news articles and the government’s white paper. Social network analysis was used to analyze the key organizations and their connections in crucial response tasks.
Three national health authorities (Central MERS Management Headquarters [CMMH], Korea Centers for Disease Control [KCDC], Ministry of Health and Welfare [MOHW]) led the response. CMMH, which did not appear in the government’s response plans, played a significant role in all 3 networks. KCDC also was involved in all 3 networks, but was most prominent in the laboratory testing network. MOHW appeared only in the patient management network. Each health authority coordinated and collaborated with distinctive types of organizations in the networks, but unclear lines of responsibilities also were found.
The study demonstrated that the roles and responsibilities of health authorities at the national level were fragmented and lacked clarity. Public health emergency preparedness must consider carefully the way to establish collaborative response systems.
Creating collaborative working and learning experiences has long been at the forefront of computer-assisted language learning research. It is in this context that, in recent years, the integration of social networking sites and Web 2.0 in learning settings has surged, generating new opportunities to establish and explore virtual communities of practice (VCoPs). However, despite the number of studies on the concept, research remains inconclusive on how learners develop a sense of community in a VCoP, and what effect this may have on interaction and learning. This research project proposes to use social network analysis, part of graph theory, to explore the configuration of a set of VCoPs, and presents an empirical approach to determine how interaction in such communities takes shape. The present paper studies the concept of “community” in two VCoPs on Facebook. Participants (Group 1: N = 123, Group 2: N = 34) in both VCoPs are enrolled in English as a foreign language courses at two Belgian institutions of higher education. Social network analysis is used to show how both learner groups establish and develop a network of peers, and how different participants in those groups adopt different roles. Participation matrices reveal that interaction mainly revolves around a number of active key figures and that certain factors such as the incorporation of online and offline assignments and the inclusion of a teacher online result in varying levels of success when establishing collaborative dialogue within the VCoPs. Recommendations are formulated to inform and improve future practice.
Chapter 5 is focused on the risk of capture of international courts by NGOs. The chapter reviews the advantages and disadvantages of NGO involvement in international courts' proceedings either as direct applicants, through filing amicus curiae briefs, or informally. Different procedures are recommended for different international courts depending on their circumstances. The second part of the chapter is focused on the reputational sanctions NGOs can create after an international court issues its judgment. Drawing on quantitative and qualitative empirical research I conducted and on insights from Social Network Analysis, the chapter argues that international courts can create conditions in which NGOs process shaming information accurately.
Chapter 5 discusses methodologies for the analysis of social groups in ancient Egypt, addressing their benefits as well as their limitations. Anthropological study of kinship has usually been undertaken in living societies, but can also be tackled for cultures no longer existing Some methodologies used for social analysis in the past include the Lévi-Straussian notion of house societies, Social Network Analysis, prosopography, or sociography. The choice of method is reliant on the type of evidence that is available; in particular, the limited number of sources in ancient Egypt favours qualitative over quantitative analysis.
For that reason, I propose a model called koinography that combines suggestions from several of these approaches. It is based on the idea that social groups, and not individuals, should be treated as the preferred unit of social analysis, and that the factor of time is a fundamental tool to explore the position and role of that group in wider society. In particular, the model of the developmental cycle of the group originally proposed by Meyer Fortes has served as inspiration for the incorporation of a more dynamic and diachronic dimension into the study of ancient Egyptian groups.
This study identifies and interprets dominant developments in the Taiwanese literary field by examining data included in publication catalogs of literary journals and supplements from 1940 to 1953. Utilizing social network analysis, it focuses on both ruptures caused by crucial political events and continuities that spanned these ruptures. The study revisits central tenets of Taiwanese literary history and, by seeking to articulate structuring principles, also unveils new perspectives on how to map and interpret the dynamics of literary systems and the ways in which they mesh with society. It thereby exemplifies how digital humanities can guide researchers toward new historical insights.
Because hard-and-fast formal rules are scarce and ethical obligations are murky, repeat players like lead plaintiff and defense attorneys can strategically play for “rules” (the shorthand term for practices that will tip the scales in their favor in future cases) in areas that affect what matter to them most. The chapter opens with Lance Cooper’s allegations in the General Motors Ignition Switch Litigation. He claimed that lead plaintiffs’ lawyers settled all their own cases confidentially before trial and cut a secret deal with GM to limit its financial exposure if plaintiffs won a big verdict. Cooper’s allegations give life to data that reveals a world open to exploitation: few rules, little oversight, multimillion dollar common-benefit fees, and a push for settlement can tempt repeat players to fill in the gaps in ways that further their own self-interest. Connected lawyers form their own groups, enforce norms, and financially sanction defectors much like a cartel would. This chapter’s empirical analysis confirms that repeat players populate plaintiff and defense leadership positions, and its social network analysis reveals that no matter what measure of centrality is used, a key group of attorneys maintains their elite position within the network and may disproportionately impact settlements.