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Since social media is increasingly pervasive in modern society, this bibliometric study aims to investigate its educational applications. Using the Scopus database, the bibliometric method analyses publications published between 2010 and 2022. The research indicates that student participation and ease of access are the two main benefits of using social media in the classroom. However, it also spreads misinformation and poses privacy and security risks. Articles that discussed how social media could be used in the classroom were found and organised using a bibliometric analysis based on their subject matter, year of publication, and authors. The research shows that between 2001 and 2020, there was a rise in the number of papers discussing the use of social media in the classroom. In addition, the top five countries in terms of annual publication output include the United States, the United Kingdom, Australia/India, and Canada. To further explore the connections between relevant articles, a co-citation network analysis was performed. Therefore, there must be strict rules and policies for using social media in education to address privacy and security concerns and the spread of false information.

The paper provides an overview of the global research on graduate education. The study applied a combination of a bibliometric and social network analysis methods to bibliographic data from Thompson Reuters' Web of Science. More specifically, a keyword search approach was used to retrieve 2,454 articles on graduate education from 1996 until 2020. The set was processed with the VantagePoint software. The paper reports the findings in the form of lists of top scholars, research centres, and countries contributing to research on graduate education. The findings include similar lists of the key funding agencies, contributing disciplines and publication venues, as well as maps representing collaborative activity in the field between institutions, and countries. Finally, the frequency of utilisation of groups of author-supplied keywords is analysed to determine the basic thematic structure of the research on the topic. The originality of the paper consists in the fact that it represents the first attempt to map the landscape of research on graduate education using bibliographic data. It can be used to supplement the results of literature reviews on the topic, which apply a more in-depth content analysis-based approaches to a limited number of papers to determine the thematic structure of the field.

Purpose: Free and open-source software (FOSS) has been used worldwide because of the advantages of user control, cost-saving, flexibility, openness, freedom, more security and better stability. The purpose of this study is to explore the status quo of educational application of FOSS and the trends from international perspectives and its implications for higher education in Hong Kong. Design/methodology/approach: The method of cluster analysis was used in this study. The Web of Science database was used as the data source and all relevant literature for the year 2010-2020 on the theme of "FOSS" was collected for analysis. The information visualization software CiteSpace was used for citation visualization analysis, revealing the research results of FOSS worldwide, including hot spots and development trends. Findings: This paper found that FOSS has become an important research area and is playing an important role in the reform and development of education. Meanwhile, the development and application of FOSS have regional imbalances and strong differentiation, including the educational sector. The paper also found that although FOSS has entered the stage of interdisciplinary development, the research and development of FOSS in the field of education is insufficient, which poses a huge challenge to decision-makers, teachers and students. Originality/value: Implications for higher education in Hong Kong including: attach importance to and vigorously promote FOSS research and practice to benefit more teachers and students; teachers and students need to be trained for acquiring the awareness and skills of FOSS applications and formulate different strategies; the government should provide greater support to formulate and implement a short and middle-term development plan to facilitate the application of FOSS; and Hong Kong higher education institutions may strengthen exchanges and cooperation with counterparts around the world to jointly promote the development of FOSS. It is hoped that the findings will provide a reference for the study and application of FOSS in higher education in Hong Kong.

Multimodal Learning Analytics (MMLA) has huge potential for extending the work beyond traditional learning analytics for the capabilities of leveraging multiple data modalities (e.g. physiological data, digital tracing data). To shed a light on its applications and academic development, a systematic bibliometric analysis was conducted in this paper. Specifically, we examine the following aspects: (1) Analyzing the yearly publication and citation trends since the year 2010; (2) Recognizing the most prolific countries, institutions, and authors in this field; (3) Identifying the collaborative patterns among countries, institutions, and authors, respectively; (4) Tracing the evolving procedure of the applied keywords and development of the research topics during the last decade. These analytic tasks were conducted on 194 carefully selected articles published since 2010. The analytical results revealed an increasing trend in the number of publications and citations, identified the prominent institutions and scholars with significant academic contributions to the area, and detected the topics (e.g. characterizing learning processes using multimodal data, implementing ubiquitous learning platforms) that received the most attention. Finally, we also highlighted the current research hotspots attempting to initiate potential interdisciplinary collaborations to promote further progress in the area of MMLA.

In 2017, the International Bureau of Education (IBE) at the United Nations Educational, Scientific and Cultural Organization (UNESCO) put forth seven global competences to address accelerating technological progress and increasing levels of complexity and uncertainty affecting many facets of society (Marope, 2017). These competences were used in examining participant discourse in a global, collaborative digital makerspace environment, where students ages 12 to 17 from six countries develop and share STEM-focused media artifacts. The participants communicate synchronously through video conference calls, referred to as online global meet-ups. The meet-ups allow students to present media artifacts they have created, share ideas, exchange information, and provide feedback. In this analysis, epistemic network analysis (ENA), a technique in quantitative ethnography, is used to examine the connections made among the IBE-UNESCO global competences in a meet-up involving participants from Finland, Kenya, and the U.S. ENA network models were created initially for the three sites, then further disaggregated by time segment to analyze how participant discourse patterns may have evolved in each context. Through this approach, the paper explores more broadly the interactive role of media making, cross-cultural engagement, and collaborative learning in the development of global competences in students.

This paper shares the work and observations from a task-based 6-week email exchange project between participants in Spain and the US. Though small in scale, the study offers insights for those interested in telecollaboration but face constraints on multiple fronts. Close examination of the exchanges reveal participants' engagement on multiple levels, including reflection on one's own culture.

Despite the widespread popularity of social networking sites (SNSs) amongst children and young people in compulsory education, relatively little scholarly work has explored the fundamental issues at stake. This paper makes an original contribution to the field by locating the study of this online activity within the broader terrain of social network theory in order to inform future educational debate and further research. The first section offers a way of classifying different kinds of online social networking and then places this within the context of the study of social networks. It is argued that relational networks create a sense of belonging and that online networks just as easily trace the contours of existing social divisions as they transcend or transform them. This analysis informs the second section which specifically addresses educational issues, including both the attractions and the limitations of such work. The paper concludes with an exploration of three possible approaches to using in SNSs in educational contexts. (Contains 1 figure.)

This paper examines the significance of the Dominion and Colonies Fund under the presidency of Frederick Paul Keppel and details ways in which the Carnegie Corporation worked to internationalize American educational theories and practices. It challenges previous scholarship claims that grants made were largely extensions of the Corporation's domestic grants within the United States and that attribute the spread of progressive models of "new education" to "key men". It considers the significance of the "key women" who served as international Carnegie contacts including Ann Gilchrist Strong, Professor of Home Science at the University of Otago, who utilized professional networks to establish herself as a conduit into universities, government policymaking, and Carnegie grant and travel programmes. Utilising a New Zealand case study, the paper then illustrates the way that Carnegie philanthropy helped to expand the work of women as domestic experts and professional social reformers within the academy and beyond. (Contains 97 footnotes.)

Literature on global international student mobility (ISM) highlights the uneven nature of student flows--from the developing to the developed world--however, studies have yet to address whether this pattern is replicated within expanding regional networks. Utilizing social network analysis, UNESCO ISM data, and World Bank income classifications, this paper examines economic inequality in ISM from 2008-2012 globally and within the Southern African Development Community, the European Higher Education Area, the Union of South American Nations, and University Mobility in Asia and the Pacific. Findings reaffirm previous global analyses which indicate that higher-income countries play a preeminent role as receivers; whereas, lower-income countries function primarily as source nations. This study demonstrates that this pattern is replicated fractally within the four regional networks as well. Globally and regionally, economically developed countries comprise the core of the world-system in tertiary education while less-developed nations are relegated to peripheral status.

In this paper, we investigate the impact of membership in the Bologna Process on patterns and driving forces of cross-national student mobility. Student exchange flows are analyzed for almost all Bologna Process member states and non-Bologna OECD members over a ten-year period (from 2000 to 2010). We apply a social network approach focusing on outbound diploma mobility. Based on social network analyses, we first visualize the exchange patterns between sampled countries. In doing so, we analyze the student exchange linkages to gain descriptive insights into the development of the network. Second, we use exponential random graph models (ERGM) to test which factors determine transnational student mobility. The results of our network analyses reveal that cross-national student exchange networks are stable over time. At the core of these networks are the USA, Great Britain, France, and Germany; they attract highest shares of students from most remaining countries in our sample. Moreover, the results of the ERGM demonstrate that homophily between countries determines student exchange patterns. The most relevant ties exist between bordering countries. Moreover, membership in the Bologna Process impacts on mobility patterns, and the effect size increases over the periods investigated.

This paper provides a network analysis of the international flow of students among 210 countries and the factors determining the structure of this flow. Among these factors, bilateral hyperlink connections between countries and the number of telephone minutes (communication variables) are the most important predictors of the flow's structure, followed by trade, the physical distance between countries, a common border between countries and a common language between two countries. The USA is by far the most central country in the flow of international students, followed by China, the UK, France, Germany, Australia and India. These results are discussed in light of World-System Theory. Future research should examine how the network of international student flows changes over time and consider additional factors to provide a better understanding of the network as an international system.

This paper provides a citation network analysis of the publications in "Studies in Higher Education" from 1976 to 2013 inclusive. This represents the entire history of the journal to date. It analyses the most published authors, most cited authors and most discussed topics using keywords. 1056 articles were taken from Web of Science[superscript SM] as a source of primary data. These articles were determined to have 32,738 references. A small percentage of these articles, 218 articles, had 1030 keywords. A data visualisation and manipulation software, Gephi, was used to provide a visual representation of the associated citation networks. We compare the results with other higher education citation analyses published elsewhere--a small, but growing area of research. Results indicate that the five most published authors throughout the journal's history are Richardson, Kember, Becher, Boud and Elton. The five most cited authors are Entwistle, Marton, Ramsden, Biggs and Becher. The five most discussed topics, using keywords, excluding higher education, are "doctoral education", "assessment", "phenomenography", "student learning" and "identity", with a number of subordinate topic clusters amongst these. Results derived from this exercise are helpful in illuminating the evolving concerns of the journal and its readership, and providing a demonstration of a rigorous analytical technique for assessing journal citation data in the future.

It's official: Online social networking is mainstream. Once the domain of teenagers and techno-geeks, sites like Facebook, LinkedIn, MySpace, and Twitter are rapidly gaining popularity with the multi-aged masses. Last year, in fact, Facebook reported its fastest growing demographic was those 25 years and older. There's no question that this new communications medium holds tantalizing possibilities for increasing and deepening alumni connections. But many alumni professionals are scratching their heads, trying to figure out where this not-so-recent phenomenon fits into an already established alumni program. Is online social networking a flashy distraction or a promising development? Should it be considered part of the regular array of alumni benefits and services, or is it separate and distinct? Why should alumni organizations jump in to this brave new world and how can they take those first steps? In this article, six alumni professionals--all early adopters of online social networking--offer their thoughts on these questions. Participating in the conversation from the United States were Andrew Shaindlin, executive director of alumni relations at California Institute of Technology; Louis Alexander, director of alumni education at the Massachusetts Institute of Technology; and Charlie Melichar, vice president for public relations and communications at Colgate University in New York. Chiming in from the U.K. were Ian Moore, head of alumni relations at Coventry University, and Ben Fitch, alumni development manager at Oxford Brookes University. And participating from Australia was Shaun McDonagh, director of marketing and communications at the University of Queensland.

Engineers of the 21st century will spend appreciable portions of their careers in environments rich with global connections. Therefore, engineering colleges and universities must develop strategies that provide the global perspectives and international experiences that will help their graduates excel in this new world order. The current paper presents some European and American approaches to creating multi-organizational, international partnerships of academic and industrial organizations that emphasize collaborative educational programmes and research efforts that meet the globalization needs of faculty members, students, and industry.

This paper describes the network of Patent and Trademark Depository Libraries (PTDLs), a collaborative partnership with the United States Patent and Trademark Office (USPTO) for disseminating patent and trademark information in every state plus the District of Columbia and Puerto Rico. Typical information sources and services provided at PTDLs are given, followed by suggestions of areas on which to focus in the future for PTDLs to continue to be vital links of information that spur economic growth, business competitiveness, and the continued discovery of new scientific and technological knowledge and applications. (Contains 2 tables.)

This paper introduces a bibliometric, citation network-based method for assessing the social validation of novel research, and applies this method to the development of high-throughput toxicology research at the US Environmental Protection Agency. Social validation refers to the acceptance of novel research methods by a relevant scientific community; it is formally independent of the technical validation of methods, and is frequently studied in history, philosophy, and social studies of science using qualitative methods. The quantitative methods introduced here find that high-throughput toxicology methods are spread throughout a large and well-connected research community, which suggests high social validation. Further assessment of social validation involving mixed qualitative and quantitative methods are discussed in the conclusion. [ABSTRACT FROM AUTHOR]

This paper relies upon the 'what's the problem represented to be?' approach to policy analysis to interrogate key representations of human trafficking implicit in the UK government's anti-trafficking policy. It identifies six policy vectors, or representations, of human trafficking embedded within the policy, including organized crime, 'illegal' immigration, and victim assistance as three primary vectors; sexual exploitation/prostitution, poverty in countries of victims' origin, and isolated instances of labour law infringements as three secondary vectors. In addition, a series of assumptions, which underlie the current interpretation of trafficking, are also identified. By exploring what the problem of human trafficking is represented to be, the paper also provides an insight into what remains obscured within the context of the dominant policy frameworks. In doing so, it highlights the role of state-capital entanglements in normalizing exploitation of trafficked, smuggled and 'offshored' labour, and critiques the UK's anti-trafficking policy for manufacturing doubt as to the structural causes of human trafficking within the context of neoliberalism. [ABSTRACT FROM AUTHOR]

Although substantial attention has focused on efforts by the new Administration to block environmental policies, climate politics have been contentious in the US since well before the election of Donald Trump. In this paper, we extend previous work on empirical examinations of echo chambers in US climate politics using new data collected on the federal climate policy network in summer 2016. We test for the similarity and differences at two points in time in homophily and echo chambers using Exponential Random Graph Models (ERGM) to compare new findings from 2016 to previous work on data from 2010. We show that echo chambers continue to play a significant role in the network of information exchange among policy elites working on the issue of climate change. In contrast to previous findings where echo chambers centered on a binding international commitment to emission reductions, we find that the pre-existing echo chambers have almost completely disappeared and new structures have formed around one of the main components of the Obama Administration’s national climate policy: the Clean Power Plan. These results provide empirical evidence that science communication and policymaking at the elite level shift in relation to the policy instruments under consideration. [ABSTRACT FROM AUTHOR]

In "Operations Research: Topics, Impact and Trends from 1952–2019," A. Calma, W. Ho, L. Shao, and H. Li retrospectively look at 68 years of publication of the Operations Research. Using 5,440 journal articles, they highlight the top contributing countries and authors and top research methods and problems investigated. Mathematical programming is the most common research method, whereas inventory is the most investigated problem. Investigations related to pricing are growing significantly. The United States, Canada, and the United Kingdom publish the most papers, with the United States and Canada having similar publication profiles per capita. Inventory is the most popular research problem studied by North American, Asian, and Middle Eastern countries, whereas European countries focus on scheduling problems. Network visualizations of the journal's last 10 years show dynamic programming as the most used method and pricing as the most studied problem. Coauthor networks on collaborations on both dynamic programming and pricing are also shown. This paper is a retrospective look at 68 years of publication output of Operations Research, revealing changes in its publications, its authors, and their impact over time and how these changes might affect researchers and practitioners in the present. A total of 5,440 journal articles from its inception in 1952 to 2019 are used. The analysis initially focuses on the most studied topics and then continues with the top research methods and research problems investigated. The top contributing countries and authors to the most investigated research problems are also studied. The results indicate that mathematical programming is the most common research method, whereas inventory is the most investigated problem. However, investigations related to pricing are growing significantly. The United States, Canada, and the United Kingdom publish the most papers, with the United States and Canada having similar publication profiles per capita. Inventory is the most popular research problem studied by North American, Asian, and Middle Eastern countries, whereas European countries focus on scheduling problems. In order to understand the latest research trend, we visualize the networks of the last 10 years of Operations Research that show dynamic programming as the most used method and pricing as the most studied problem. We further visualize the coauthor networks on both dynamic programming and pricing to identify the most significant clusters of researchers and the topics these research clusters collaborate on. Finally, we provide researchers information about where Operations Research is and where it is likely heading. [ABSTRACT FROM AUTHOR]

A review of energy subsidy research from a bibliometric perspective was conducted. Based on the bibliometric method, a statistical analysis of energy subsidy–related publications from 1997 to 2016 was undertaken using the Science Citation Index (SCI) and Social Science Citation Index (SSCI) databases. A total of 1182 publications were retrieved, with a significant increase in the number of publications observed after 2006. The majority of these publications were within the disciplines of Energy & Fuels and Environmental Science & Ecology. Although the USA and China contributed the most papers, authors from 96 countries were involved in the various studies. The USA was the center of global collaborations, while other countries/territories mainly conducted bilateral or regional collaborations in their research activities. Five of the top 11 most productive institutes were from China, followed by the USA. The frequency of collaborations among institutes was relatively low. However, the institute–keyword 2-mode network showed that institutes had great potential to cooperate on a number of common topics. Five major themes were identified from the co-keywords analysis: general renewable energy research, bio-energies, sustainability, subsidies, and welfare. The findings, as a complement to previous conventional reviews, will be useful in future energy subsidy research. [ABSTRACT FROM AUTHOR]

Based on coupled networks, taking node load, capacity and load redistribution between two networks into consideration, we propose functionally identical coupled networks, which consist of two networks connected by interlinks. Functionally identical coupled networks are derived from the power grid of the United States, which consists of many independent grids. Many power transmission lines are planned to interconnect those grids and, therefore, the study of the robustness of functionally identical coupled networks becomes important. In this paper, we find that functionally identical coupled networks are more robust than single networks under random attack. By studying the effect of the broadness and average degree of the degree distribution on the robustness of the network, we find that a broader degree distribution and a higher average degree increase the robustness of functionally identical coupled networks under random failure. And SF-SF (two coupled scale-free networks) is more robust than ER-ER (two coupled random networks) or SF-ER (coupled random network and scale-free network). This research is useful to construct robust functionally identical coupled networks such as two cooperative power grids. [ABSTRACT FROM AUTHOR]

The current paper aimed to investigate the network structure and centrality indexes of hypersensitive narcissism using the hypersensitive Narcissism Scale (HSN). Additionally, we aimed to explore its relationships with dark triad personality aspects. A globally diverse sample of “53,981” participants (47.9% non-United States responders) completed the HSN and Dark Triad Dirty Dozen scale (DTD). We estimated the network structure across genders to determine the core characteristics of hypersensitive narcissism. Additionally, bridge and central nodes (characteristics) were identified. All analyses were performed using R-Studio programming software. The network comparison test indicated significant differences in the network structures between males and females (Network-Invariance: 0.0489, P < 0.01; Global Strength Invariance: 0.101, P < 0.01). In the network of HSN for male participants, characteristics with the highest strength centrality were “Highly affected by criticism” (HSN.2, strength = 1.08) and “Self-absorbed in personal pursuits” (HSN.8, strength = 1.28). For female participants, “Self-absorbed in personal pursuits” (HSN.8, strength = 1.32) and “privately annoyed by others’ needs” (HSN.10, strength = 1.21) were the highest central characteristics. The assessment of bridge strength indicated that nodes HSN.2 (Highly sensitive to criticism), scoring 0.42, and DTD.1 (Tendency to manipulate for gain, a component of Machiavellianism), scoring 0.428, showed the highest bridge strength values. The current study identified core characteristics of hypersensitive narcissism and its correlation with dark triad personality, revealing gender-specific patterns and bridging symptoms between the two constructs. These findings showed that focusing on these core characteristics may be advantageous in treating individuals exhibiting elevated levels of narcissism. [ABSTRACT FROM AUTHOR]

Dynamic Stochastic General Equilibrium (DSGE) models are widely used as a tool for policy decision-making. These models lost their fame when they could not predict the crisis in 2008 and could not address policy problems afterward. Meanwhile, the Agent-Based Modelling (ABM) approach emerged as an alternative to DSGE models. Between 2000 and 2020, this study examined scholarly research on the topic of ABM in economics. The information is gathered using the SCOPUS database. Numerous bibliometric indicators are provided, including the total number of publications and citations. The study reveals that agent-based modelling in economics research has grown in recent years. The majority of active research occurs in countries such as the United States of America, and collaboration allows researchers to reach out to many more countries. ABM has the potential to be applied in a wide range of economic fields. ABM also necessitates research into its own development to be used to better understand economic phenomena. [ABSTRACT FROM AUTHOR]

This paper aims to analyze confidence-building measures (CBMs) for cyberspace taking place in Northeast Asia. Accordingly, it explores features of cyber security in the Northeast Asian region and concepts of CBMs for cyberspace. Then, it studies networks of CBMs for cyberspace that took place on the government level in the region from 2009 through the first half of 2014 by using the network analysis method, which is useful for studying current social relations. This study analyzes the structure of CBMs networks used in the region for the past six years and the actors. Conclusions of this study are as follows: First, CBMs for cyberspace in Northeast Asia are focused on the United States. Second, the CBMs in the region have similar features to those of traditional security cooperation. Thirdly, they are strongly based on realism. From the perspective of networks, this study is meaningful in that it used a macro approach to analyze CBMs, which was difficult to perform by using conventional methods. [ABSTRACT FROM AUTHOR]

Drawing on recent contributions inferring financial interconnectedness from market data, our paper provides new insights on the evolution of the US financial industry over a long period of time by using several tools coming from network science. Relying on a Time-Varying Parameter Vector AutoRegressive (TVP-VAR) approach on stock market returns to retrieve unobserved directed links among financial institutions, we reconstruct a fully dynamic network in the sense that connections are let to evolve through time. The financial system analysed consists of a large set of 155 financial institutions that are all the banks, broker-dealers, insurance and real estate companies listed in the Standard & Poors’ 500 index over the 1993–2014 period. Looking alternatively at the individual, then sector-, community- and system-wide levels, we show that network sciences’ tools are able to support well-known features of the financial markets such as the dramatic fall of connectivity following Lehman Brothers’ collapse. More importantly, by means of less traditional metrics, such as sectoral interface or measurements based on contagion processes, our results document the co-existence of both fragmentation and integration phases between firms independently from the sectors they belong to, and doing so, question the relevance of existing macroprudential surveillance frameworks which have been mostly developed on a sectoral basis. Overall, our results improve our understanding of the US financial landscape and may have important implications for risk monitoring as well as macroprudential policy design. [ABSTRACT FROM AUTHOR]

Fish consumption in Mexico is considered low (around 12 kg per person per year) and non-homogeneously distributed across the country. One of the reasons for this situation is the scarcity of wholesale selling sites. In this context, the Mercado del Mar (MM), located in Guadalajara city, Jalisco, is the second biggest wholesale fish market in Mexico, with a distribution of about 500 tons per day and a variety of about 350 different species of fish. In this paper, we argue that MM has accumulated social capital, which is formed from two main resources: buyer and seller relationships, and reputation. Specifically, the MM manages a broad and intensive interaction among business actors and the already achieved reputation allows the MM to adapt to market changes. To validate our hypotheses, an empirical study was conducted in 2015 by means of interviews to fish wholesalers in the MM and a sample of their suppliers and buyers. For simplicity we have only considered fresh water fish. We have followed snow-ball sampling as the survey strategy. Results show that the MM has responded to fish market dynamics organizing a complex network of buyers and suppliers whose relationships can be explained in the form of strong and weak ties. At the same time, reputation has been the central resource to build this social capital and also gives place to market transactions. Additionally, the strategic position of Guadalajara city and the well-connected routes have facilitated fish bulking and distribution in the region. [ABSTRACT FROM AUTHOR]

The social functions of urbanized areas are highly dependent on and supported by the convenient access to public transportation systems, particularly for the less privileged populations who have restrained auto ownership. To accurately evaluate the public transit accessibility, it is critical to capture the spatiotemporal variation of transit services. This can be achieved by measuring the shortest paths or minimum travel time between origin-destination (OD) pairs at each time-of-day (e.g. every minute). In recent years, General Transit Feed Specification (GTFS) data has been gaining popularity for between-station travel time estimation due to its interoperability in spatiotemporal analytics. Many software packages, such as ArcGIS, have developed toolbox to enable the travel time estimation with GTFS. They perform reasonably well in calculating travel time between OD pairs for a specific time-of-day (e.g. 8:00 AM), yet can become computational inefficient and unpractical with the increase of data dimensions (e.g. all times-of-day and large network). In this paper, we introduce a new algorithm that is computationally elegant and mathematically efficient to address this issue. An open-source toolbox written in C++ is developed to implement the algorithm. We implemented the algorithm on City of St. George’s transit network to showcase the accessibility analysis enabled by the toolbox. The experimental evidence shows significant reduction on computational time. The proposed algorithm and toolbox presented is easily transferable to other transit networks to allow transit agencies and researchers perform high resolution transit performance analysis. [ABSTRACT FROM AUTHOR]

There have been intense debates regarding which industrial sectors should be prioritized for receiving bailout in economic recessions. This paper takes a network perspective to rank sectors according to the Power-of-Pull (PoP), i.e. a sector's power to pull the overall economy. An eigenvector method is employed to assess the PoP of sectors in the USA, using input–output data from 1998 to 2010. The results support bailout to the motor vehicle sector, but argue against bailout to public infrastructure, health care and information technologies design and service sectors, and also reveal the continual decline of PoP ranking of computer and electronics manufacturing sector over time. These results confirm some but also show little support to some other economic revival policies of the Obama Administration in the USA. [ABSTRACT FROM PUBLISHER]

In this paper, we extend some usual techniques of classification resulting from a large-scale data-mining and network approach. This new technology, which in particular is designed to be suitable to big data, is used to construct an open consolidated database from raw data on 4 million patents taken from the US patent office from 1976 onward. To build the pattern network, not only do we look at each patent title, but we also examine their full abstract and extract the relevant keywords accordingly. We refer to this classification as semantic approach in contrast with the more common technological approach which consists in taking the topology when considering US Patent office technological classes. Moreover, we document that both approaches have highly different topological measures and strong statistical evidence that they feature a different model. This suggests that our method is a useful tool to extract endogenous information. [ABSTRACT FROM AUTHOR]

This study presents measures to evaluate the power of states from a network perspective. Several indicators have been used for such analysis, including GDP, GNP, and the CINC. However, these indicators have limitations in that they do not take into account relational factors. Therefore, we provide three measures developed from a network perspective at the macro, meso, and micro levels to overcome these limitations. Furthermore, we explore the applicability of network theory-based measurement by analyzing changes in network power in the United States and China and present the following results. First, considering the economic domain, we conclude that China has surpassed the United States at the micro level, and the results of the centrality analysis indicate that the United States and China are very close at the other two levels. Second, in the military trade and cultural trade sectors, the United States has consistently been the most powerful state at all levels. [ABSTRACT FROM AUTHOR]

This research paper aims to better understand the network structure of higher education in North America. It draws on a relationally networked dataset of 1,292 degree-granting colleges and universities in North America to develop a modularity class approach to categorizing colleges and universities based on their own self-defined peer networks and assesses the utility of the modularity class approach as well as several measures of network centrality for predicting offerings of new curricular fields. Results show that not all measures of network centrality equally predict organizational change outcomes, with hub/authority position being most important. Additionally, results show that an empirically derived modularity class approach to categorizing organizations has important strengths in relation to more typical approaches based on prestige or perceived organizational characteristics. The approaches detailed in this paper will be useful for future analysts seeking to explain the spread of innovations and behavior across the higher education institutional field, as well as those seeking to understand clustering and organizational divergence. [ABSTRACT FROM AUTHOR]

With the emergence of smartphones, the paradigm of the mobile ecosystem has changed rapidly. In particular, global mobile firms focus on technological competition when jostling for market position in recognition of the strategic need to secure a strong mobile platform. In this paper, we analyse the network structure of technological knowledge flows in mobile ecosystems using US patent citation information. We find that two subsectors, platform providers and application and software providers, are at the centre of knowledge exchange activity and play a brokerage role as the key knowledge mediator. Then, we categorise mobile firms into five different groups based on the patterns of their network centrality: knowledge keystone players, knowledge-distributing mediators, knowledge-absorbing mediators, catch-up players, and pure knowledge receivers. The categorisation of firms demonstrates that knowledge flows in the mobile industry converge towards a few leading firms, and such patterns are shaping the mobile ecosystem with respect to technological knowledge. The firms categorised as catch-up players have played a brokerage role within their group, while the firms categorised as knowledge keystone players play a brokerage role across different groups. [ABSTRACT FROM PUBLISHER]

This article uses Exponential Random Graph Models (ERGMs) to advance strategic management research, focusing on an application to board interlock network tie formation. Networks form as the result of actor attributes as well as through the influence of existing ties. Conventional regression models require assumptions of independence between observations, and fail to incorporate endogenous structural effects of the observed network. ERGMs represent a methodological innovation for network formation research given their ability to model actor attributes along with endogenous structural processes. We illustrate these advantages by modeling board interlock formation among Fortune 100 firms.We also demonstrate how ERGMs offer significant opportunities to extend existing strategy research and open new pathways in multiparty alliances, microfoundations of interorganizational network formation, and multiplexity of ties among actors. Managerial summary: Social networks are increasingly important in the business world, not only between individuals but also between organizations. Firms can obtain information, resources, and status through their external network connections, and understanding how these outside ties form is an important goal of strategy research. Our paper helps advance this effort by introducing a new tool for social network analysis, Exponential Random Graph Models (ERGMs) to the management and strategy fields. We provide an example of this method, demonstrating how social network ties form between companies when they hire common directors to their boards. Executives can benefit from this research through a greater understanding of how corporate relationships are built with allies as well as among competitors. [ABSTRACT FROM AUTHOR]

In 1939, the Futurama exhibit at the New York World's Fair amazed visitors with its diorama showing futuristic freeways crossing the countryside and reshaping cities. After the fair, the exhibit's designer, Norman Bel Geddes, elaborated the model into a proposal for a national freeway network. This paper examines the network structure and geographic dimensions of Bel Geddes's vision and compares it to the Interstate Highway System, created several years later. Despite the futuristic trappings inherited from the Futurama model, the two networks are surprisingly similar except in their relation to cities, which Bel Geddes's network avoids. The majority of elements in Bel Geddes's system have been incorporated into actual routes and networks, and it can be expected that his system would have gone through many of the same adaptations to changing economic, environmental, and political circumstances as the Interstate Highway System. [ABSTRACT FROM AUTHOR]

An analysis of who owns large companies and how they are organised is overdue in the study of Latin American elites, especially at transnational level. It is a limitation that has hampered debates on the emergence of transnational business elites in the region. This paper identifies the owners of the largest companies in Latin America and analyses the networks they form. The results reveal the formation of an interlocking ownership network between a small number of transnational owners, most of whom are financial corporations in the United States and Europe. These findings allow us to discuss regional integration and the dominance of economic models imported from those territories. [ABSTRACT FROM AUTHOR]

How is know ledge distributed over space and how are different types of knowledge related? These questions have so far received little attention . In this paper we measure knowledge relatedness based on the relationship between individual patent categories by using co-classification information obtained from EPO patents. We also follow specialization of countries and its evolution over the past three decades. We focus on the EU, the United States and China. The objective of this paper is to identify the knowledge relatedness between technological fields and to map know ledge produced in selected countries. For visualization of knowledge relatedness network analysis has been used. [ABSTRACT FROM AUTHOR]

• A first empirical analysis of the relationships between capital centralization, monetary policy guidelines, and the business cycle. • A tightening monetary policy brings about a higher centralization of capital. • A 1% increase in the policy rate brings about a reduction in the fraction of top shareholders of net control of about 13% in the US and of 5% in the EA. • A higher centralization of capital, in turn, leads to a reduction of GDP with respect to its trend. • A 1% decrease in the fraction of top shareholders leads to a 2.3% and 1.5% contraction of the nominal GDP deviation from its trend in the US and in the EA. Based on a connection between network analysis and B-VAR models, this paper provides a first empirical evidence of the relationships between capital centralization expressed in terms of network control on one hand and monetary policy guidelines and business cycles on the other. Our findings suggest that a tightening monetary policy leads to a decrease in the fraction of top shareholders of network control which results in a higher centralization of capital; and that a higher centralization of capital, in turn, leads to a reduction of GDP with respect to its trend. These relations are confirmed both for the United States and the Euro Area. [ABSTRACT FROM AUTHOR]

• Child maltreatment is a complex problem requiring interdisciplinary collaboration. • A fellowships program was designed to support maltreatment prevention scholars. • The program created a densely connected interdisciplinary network of fellows. • Scientific collaborations between fellows increased over time. Child maltreatment is a complex problem requiring interdisciplinary collaborative research to generate innovative solutions. The Doris Duke Fellowships for the Promotion of Child Well-Being were designed to identify and nurture emerging scholars committed to child maltreatment prevention and create a supportive interdisciplinary learning network. This paper examines connectivity within the collaborative network created by the fellowships program using longitudinal social network data. Participants were 120 individuals selected as Doris Duke Fellows during their doctoral training at universities in the United States. Fellows completed annual, voluntary web-based surveys to assess their interactions with other fellows during the past year. Social network analysis methods were used to assess the strength and quality of the learning network over a four-year period. Across four years of data, there were increases in the number of connections, proportion of cross-cohort connections, and proportion of interdisciplinary connections. Network analyses showed a highly connected network consisting of primarily medium- and high-quality connections between fellows from different disciplines. The number of scientific journal articles authored by two or more fellows grew substantially over time. Findings indicate the collaborative network created by the fellowships program is growing and strengthening over time. The new Child Well-Being Research Network extends the fellowships network to a broader group of scholars and professionals to advance diversity, equity, inclusion, and justice in the field of child well-being research. [ABSTRACT FROM AUTHOR]

The United States (U.S.) swine industry has struggled to control porcine reproductive and respiratory syndrome (PRRS) for decades, yet the causative virus, PRRSV‐2, continues to circulate and rapidly diverges into new variants. In the swine industry, the farm is typically the epidemiological unit for monitoring, prevention, and control; breaking transmission among farms is a critical step in containing disease spread. Despite this, our understanding of farm transmission still is inadequate, precluding the development of tailored control strategies. Therefore, our objective was to infer farm‐to‐farm transmission links, estimate farm‐level transmissibility as defined by reproduction numbers (R), and identify associated risk factors for transmission using PRRSV‐2 open reading frame 5 (ORF5) gene sequences, animal movement records, and other data from farms in a swine‐dense region of the U.S. from 2014 to 2017. Timed phylogenetic and transmission tree analyses were performed on three sets of sequences (n = 206) from 144 farms that represented the three largest genetic variants of the virus in the study area. The length of inferred pig‐to‐pig infection chains that corresponded to pairs of farms connected via direct animal movement was used as a threshold value for identifying other feasible transmission links between farms; these links were then transformed into farm‐to‐farm transmission networks and calculated farm‐level R‐values. The median farm‐level R was one (IQR = 1–2), whereas the R value of 28% of farms was more than one. Exponential random graph models were then used to evaluate the influence of farm attributes and/or farm relationships on the occurrence of farm‐to‐farm transmission links. These models showed that, even though most transmission events cannot be directly explained by animal movement, movement was strongly associated with transmission. This study demonstrates how integrative techniques may improve disease traceability in a data‐rich era by providing a clearer picture of regional disease transmission. [ABSTRACT FROM AUTHOR]

This paper explores the conditions under which local governments are likely to engage in formalized intergovernmental developmental cooperation. The author theorizes that policy competition, informational and divisional transaction costs, and resources condition the likelihood of institutional collective action. Data from a variety of sources—including a unique author-conducted survey of local officials in Colorado—are used to test hypotheses in a dyadic model of local cooperation. Results indicate that agreements are more likely in competitive policymaking environments and when jurisdictions have more informational resources. [ABSTRACT FROM PUBLISHER]

Understanding the nature of migratory behaviors within animal populations is critical to develop and refine conservation and management plans. However, tracking migratory marine animals across life stages and over multiple years is inherently difficult to achieve, especially for highly migratory species. In this paper, we explore the use of acoustic telemetry to characterize the spatial ecology of Atlantic tarpon ( Megalops atlanticus ), elucidate the ecology of this poorly studied species, and ultimately inform conservation and management. Using the data from twenty-two acoustically tagged Atlantic tarpon, we found a diversity of tarpon migratory patterns, including spatial and temporal overlap for some individuals. We also reveal fine scale movements within specific ecosystems, as well as a range of distributions and connectivity across coastal waters of the southeastern United States of America. For tarpon with tracking durations greater than one month (n = 13), we found heterogeneous space use and migratory connectivity with some tarpon remaining close to their capture location while others migrated hundreds of kilometers. In addition, we were able to identify a northern and southern limit for one migratory tarpon that had detections spanning over 365 days. We share analyses on Atlantic tarpon data, including model-driven approaches and network analysis, to investigate movement strategies and space use, which may be pertinent to other studies involving highly migratory species. The project was a collaborative effort involving several acoustic telemetry networks which enabled the monitoring of broad- and fine-scale movements for extended periods of time that would normally be difficult to achieve with other monitoring techniques. Although challenges exist with applying acoustic telemetry to monitor highly migratory species, we also discuss its value in enabling researchers to assess movements and space use beyond the focal species, such as cross-ecosystem comparisons and multi-species interactions. [ABSTRACT FROM AUTHOR]

The U.S. airline network is one of the most advanced transportation infrastructures in the world. It is a complex geospatial structure that sustains a variety of dynamics including commercial, public, and military operations and services. We study the U.S. domestic intercity passenger air transportation network using a weighted complex network methodology, in which vertices represent cities and edges represent intercity airline connections weighted by average daily passenger traffic, non-stop distance, and average one-way fares. We find that U.S. intercity passenger air transportation network is a small-world network accompanied by dissortative mixing patterns and rich-club phenomenon, implying that large degree cities (or hub cities) tend to form high traffic volume interconnections among each other and large degree cities tend to link to a large number of small degree cities. The interhub air connections tend to form interconnected triplets with high traffic volumes, long non-stop distances, and low average one-way fares. The structure of the U.S. airline network reflects the dynamic integration of pre-existing urban and national transportation infrastructure with the competitive business strategies of commercial airlines. In this paper we apply an emerging methodology to representing, analyzing, and modeling the complex interactions associated with the physical and human elements of the important U.S. national air transport and services infrastructure. [ABSTRACT FROM AUTHOR]