Journal Citation Network Research Articles

Surveying the landscape of environmental social science: a bibliometric and network analysis

Social science research on the environment has grown exponentially in the past four decades alongside increasing awareness that environmental risks, such as climate change, cannot be understood by natural science interventions alone. While prior research examines how specific disciplines, like sociology, have attended to the environment or how specific problems have been engaged across disciplines, less attention has been offered to the entire landscape of research on the environment in the social sciences. In this article, we ask: What is the landscape of environmental social science? Focusing on 124,906 social scientific articles from the Web of Science, we analyze the relationship between journals publishing research on the environment. Specifically, we construct journal citation networks and topic models on bibliographic records from 1990 to 2022. Results suggest that journals form coherent communities associated with both disciplinary and interdisciplinary research topics, indicating that journal communities may be a central organizing feature of ESS. Moreover, research topics prevalent in this field have changed over time, potentially in relation to the ongoing neoliberalization of climate change politics. As scholars want to influence policy and industrial practice, their research implicitly reflects values consistent with the current political economic order. We conclude by highlighting the implications of these findings for the field of environmental social science.

Development of bioenergy technologies: A scientometric analysis

Bioenergy has the potential to substitute the current demand for fossil fuels in various applications. Recovering energy from bio-based materials due to environmental considerations has been adopted as a policy objective by governments and international organizations, which led to both vast financial investment and scientific research, especially in the last two decades. So far, various feedstocks and technologies have been scrutinised by the research community, although not all of them are commercially adopted due to sustainability considerations. This study employs scientometric analysis to survey the progress of scientific development in the field of bioenergy from 1966 to 2022, using ten parameters including publication year, type of document, categories, countries, affiliations, document citations, co-authorship, author citation networks, journal citation networks, and keywords. A total of 51,905 scientific documents were collected from the Web of Science, involving more than 96,000 authors from 162 countries. The dispersion of studies followed an ascending distribution with a sharp increase in the second half of the 2000s. The evolution of keywords in terms of burst strength confirmed the advancements of technologies from primary first-generation to advanced fourth-generation bioenergies. Based on the evolution of science in this area, it is concluded that integrated sustainability assessment studies, covering technical, economical, environmental, and social aspects, are needed to bridge the gap between abundant theoretical endeavours and limited commercial use of this energy source.

The Weight of Surgical Knowledge: Navigating Information Overload.

The Weight of Surgical Knowledge: Navigating Information Overload.

REVIEW OF DIGITAL MARKETING LITERATURE BY BIBLIOMETRIC AND VISUALIZATION ANALYSIS

The study aims to examine the publications related to digital marketing published in 1985- 2021 with the social network analysis method and to reveal the research trends in the digital marketing field. For this aim, publications with “digital marketing” in the title were scanned in the Scopus database. In the study, bibliometric data of 469 publications downloaded from the Scopus database were used. Bibliometric analysis was carried out for publication language, publication year, publication types, journal citation network, keyword and subject trends, and author co-citation network. According to the results, the interest in the digital marketing research field has increased since 2017. Publications mainly consist of conference proceedings and articles. The languages of the publications are English, Portuguese, and Spanish. The countries of origin of the publications are India, America, and the United Kingdom. While the Digital Marketing journal is the most frequently cited journal, Kannan and Li (2017) is identified it as the most cited paper. The interests of young adults, evolving big data, and consumer buying behavior are the most studied topics. The most commonly used keywords in publications were digital marketing, marketing, commerce, social media, sales, social networks, human, artificial intelligence, internet, and big data.

Node2vec Representation for Clustering Journals and as A Possible Measure of Diversity

Abstract Purpose To investigate the effectiveness of using node2vec on journal citation networks to represent journals as vectors for tasks such as clustering, science mapping, and journal diversity measure. Design/methodology/approach Node2vec is used in a journal citation network to generate journal vector representations. Findings 1. Journals are clustered based on the node2vec trained vectors to form a science map. 2. The norm of the vector can be seen as an indicator of the diversity of journals. 3. Using node2vec trained journal vectors to determine the Rao-Stirling diversity measure leads to a better measure of diversity than that of direct citation vectors. Research limitations All analyses use citation data and only focus on the journal level. Practical implications Node2vec trained journal vectors embed rich information about journals, can be used to form a science map and may generate better values of journal diversity measures. Originality/value The effectiveness of node2vec in scientometric analysis is tested. Possible indicators for journal diversity measure are presented.

Citation Network Analysis of Dental Implant Literature from 2007 to 2016

This bibliometric study analyzed English language dental implant literature from 2007 to 2016 to evaluate and identify the terms, authors, and journals concerning dental implant articles with high citation count and the structure of their bibliometric networks. The Web of Science database was searched to identify articles on the topic of dental implants published under the Web of Science category of Dentistry, Oral Surgery & Medicine from 2007 to 2016. The articles were first assessed using descriptive analysis concerning the authors, organizations, countries/territories, and journals. Afterward, VOSviewer was used to visualize the term map, author network, and journal network consisting of the most highly cited entities. CiteSpace II was used with default settings to identify keywords that experienced a large increase in citations received within the surveyed period of time. The citation analyses were based on 12,114 dental implant articles published during the survey period. The top five highly cited terms with > 500 publication counts were peri-implantitis (a mean of 20.17 citations per surveyed article [CPA]), survival rate (19.02 CPA), survival (18.74 CPA), implant failure (16.58 CPA), and success rate (16.53 CPA). The top five authors with highest average citations authored 80 papers (80/12,114 = 0.7%) that received 5,962 citations (5,962/151,404 = 3.9%) among the highly cited authors' network. Clinical Oral Implants Research had the largest total number of citation links (19,283), and hence, was in the center of the journal network, with a mean of 21.47 citations per surveyed article. The terms with high impact were related to implant success, survival, failure, and peri-implantitis. Clinical Oral Implants Research and The International Journal of Oral & Maxillofacial Implants were in the center of the journal citation network.

Stochastic block model reveals maps of citation patterns and their evolution in time

Abstract In this study we map out the large-scale structure of citation networks of science journals and follow their evolution in time by using stochastic block models (SBMs). The SBM fitting procedures are principled methods that can be used to find hierarchical grouping of journals that show similar incoming and outgoing citations patterns. These methods work directly on the citation network without the need to construct auxiliary networks based on similarity of nodes. We fit the SBMs to the networks of journals we have constructed from the data set of around 630 million citations and find a variety of different types of groups, such as communities, bridges, sources, and sinks. In addition we use a recent generalization of SBMs to determine how much a manually curated classification of journals into subfields of science is related to the group structure of the journal network and how this relationship changes in time. The SBM method tries to find a network of blocks that is the best high-level representation of the network of journals, and we illustrate how these block networks (at various levels of resolution) can be used as maps of science.

Bi-directional h-index: A new measure of node centrality in weighted and directed networks

Abstract This paper builds an index family, named bi-directional h-index, to measure node centrality in weighted directed networks. Bi-directional h-index takes the directed degree centrality as the initial value and iteratively uses more network information to update the node’s importance. We prove the convergence of the iterative process after finite iterations and introduce an asynchronous updating process that provides a decentralized, local method to calculate the bi-directional h-index in large-scale networks and dynamic networks. The theoretical analysis manifests that the bi-directional h-index is feasible and significant for establishing a greater conceptual framework that includes some existing index concepts, such as lobby index, node’s h-index, c-index and iterative c-index. An example using journal citation networks indicates that the bi-directional h-index is different from directed degree centrality, directed node strength, directed h-degree and the HITS algorithm in ranking node importance. It is irreplaceable and can reflect these measures of node’s importance.

Betweenness and diversity in journal citation networks as measures of interdisciplinarity\u2014A tribute to Eugene Garfield

Journals were central to Eugene Garfield’s research interests. Among other things, journals are considered as units of analysis for bibliographic databases such as the Web of Science and Scopus. In addition to providing a basis for disciplinary classifications of journals, journal citation patterns span networks across boundaries to variable extents. Using betweenness centrality (BC) and diversity, we elaborate on the question of how to distinguish and rank journals in terms of interdisciplinarity. Interdisciplinarity, however, is difficult to operationalize in the absence of an operational definition of disciplines; the diversity of a unit of analysis is sample-dependent. BC can be considered as a measure of multi-disciplinarity. Diversity of co-citation in a citing document has been considered as an indicator of knowledge integration, but an author can also generate trans-disciplinary—that is, non-disciplined—variation by citing sources from other disciplines. Diversity in the bibliographic coupling among citing documents can analogously be considered as diffusion or differentiation of knowledge across disciplines. Because the citation networks in the cited direction reflect both structure and variation, diversity in this direction is perhaps the best available measure of interdisciplinarity at the journal level. Furthermore, diversity is based on a summation and can therefore be decomposed; differences among (sub)sets can be tested for statistical significance. In the appendix, a general-purpose routine for measuring diversity in networks is provided.

Discovering interdisciplinary interactions between two research fields using citation networks

As more and more interdisciplinary areas are emerging at a quick pace, analysis of interdisciplinary interactions among disciplines is of great importance. Citation network analysis is advancing as a tool to extricate policy implications from scientific as well as patent literature. Most of the studies related to interdisciplinarity under the lens of network analysis were concentrated mainly on journal–journal citation networks. Citation networks of articles reflect the accumulation as well as flow of knowledge. Therefore, specific developments that might cause interdisciplinary evolution can be identified. Due to this underexplored potential, we attempt to investigate interdisciplinarity at the level of published articles. As the interdisciplinary interactions among two disciplines is reflected by common/boundary papers and the arcs of cross-disciplinary citations, a quantitative methodology for assessing the strength of interdisciplinary interactions, dominant mode of interaction, mutual contribution, etc., is developed based on these. Interdisciplinary interactions among the fields ‘biotechnology for energy’ and ‘nanotechnology for energy’ is chosen as a case study. The existence of ‘mutual contribution’ among these fields is identified. ‘Biotechnology for energy’ is found to contribute more to the development of ‘nanotechnology for energy’ than vice versa. Important specific developments associated with interdisciplinary interactions are also explored using qualitative decision rules. Quantitative as well as qualitative methods devised in this paper form a framework for interdisciplinarity assessment that can be used by various decision makers.

Food safety as a field in supply chain management studies: a systematic literature review

The increasing number of food contamination events has called the attention of both practitioners and scholars to food safety problems and their consequences. Many of these events are related to the supply chain because food production is now a global process of commoditized goods, made by large corporations that purchase inputs from producers in many countries. Given the linkage between supply chain and food safety issues, we investigated how studies in the supply chain management area have examined food safety issues, exploring some of their important characteristics. To do so, we conducted a systematic literature review of 46 papers, published in 23 journals, indexed in the Web of Science database. As a result, we pointed out some main characteristics of these papers, including journal attributes, authorship data, citation network, methodological characteristics, and theoretical approaches. Results serve as a reference to scholars and allow us to discuss some potential opportunities for future research in the field of food safety in the supply chain management area.

융합 학문으로서의 산업공학 : 학술지 인용 네트워크 분석을 활용한 산업공학의 학문적 융합 구조 탐색

One of the distinctive characteristics of industrial engineering (IE) is its multidisciplinarity. This paper explores the multidisciplinary nature of IE using journal citation network analysis. Using the relatedness indexes of IE journals obtained from journal citation report (JCR), we firstly construct the IE network only composed of 26 IE journals. The resulting IE network is partitioned into three sub-networks: management engineering, manufacturing/quality, and ergonomics. We then propose the IE convergence network which includes 81 related journals in other disciplines as well as 26 IE journals. Scrutinizing the IE convergence network reveals that IE has a high degree of interactions with seven disciplines : Operations Research and Management Science, Statistics and Probability, Manufacturing Engineering, Computer Science, Engineering Design, Business Management, Human Factors and Ergonomics. We investigate the contributions of the related disciplines to IE as well as contributions of IE to the related disciplines. The role of IE journals in exchanging knowledge with related disciplines is also identified by brokerage analysis. It is shown that visualizing and analyzing the IE convergence network can provide an excellent overview of the multidisciplinary structure of IE, which can help IE researchers easily grasp the state-of-the art of IE research.

Exploring the intellectual structure of nanoscience and nanotechnology: journal citation network analysis

Understanding the research trends and intellectual structure of nanoscience and nanotechnology (nano) is important for governments as well as researchers. This paper investigates the intellectual structure of nano field and explores its interdisciplinary characteristics through journal citation networks. The nano journal network, where 41 journals are nodes and citation among the journals are links, is constructed and analyzed using centrality measures and brokerage analysis. The journals that have high centrality scores are identified as important journals in terms of knowledge flow. Moreover, an intermediary role of each journal in exchanging knowledge between nano subareas is identified by brokerage analysis. Further, the nano subarea network is constructed and investigated from the macro view of nano field. This paper can provide the micro and macro views of intellectual structure of nano field and therefore help researchers who seek appropriate journals to acquire knowledge and governments who develop R&D strategies for nano.

Mapping the field of educational administration research: a journal citation network analysis

PurposeThe purpose of this study is to uncover how knowledge is exchanged and disseminated in the educational administration research literature through the journal citation network.Design/methodology/approachDrawing upon social network theory and citation network studies in other disciplines, we constructed an educational administration journal citation network by extracting all 157,372 citations from 5,359 journal articles in 30 educational administration journals from 2009 to 2013. We then performed social network analysis to visualize the network structure by journal clusters, and quantified journal prominence and interdisciplinarity by calculating Freeman indegree and betweenness, respectively. In addition to journal-to-journal citations, we examined the sources of non-journal citations by citation counts.FindingsThe results of journal prominence, interdisciplinarity, and eight journal clusters in the citation network indicate that educational administration, as a porous field, intimately interacts with the sub-fields of education (e.g., urban education and teacher education), other disciplines (e.g., economics, human resources, sociology, and psychology), and the research internationally. In addition to journals as the knowledge source (45.29%), we also found books (31.08%) and reports (14.98%) are important citation sources in the educational administration research literature. The most cited books and reports shed light on the knowledge base in the theory, research, and practice of educational administration.Originality/valueThe results of this by far the largest-scale study of educational administration journals present abundant evidence that educational administration is a porous field. This study also presents social network analysis as an alternative method to evaluate journal influence in the educational administration field.

Scholarly Communication in AERA Journals, 1931 to 2014

Scientific disciplines build on social structures, such as scholarly associations and scholarly journals, that facilitate the formation of communities of specialists. Analyses of such social structures can thus also be used to shed light on the morphogenesis of scientific specializations. The authors analyze how two journals of the American Educational Research Association, the Review of Educational Research and the American Educational Research Journal, organized communication around education in the period between 1931 and 2014. The authors focus on three interrelated aspects: (a) the changing structures of authority and authorship, (b) the national-versus-global orientation of these journals and of the association, and (c) the features of the citation networks of both journals and the ties between education research and other fields of research, especially psychology and sociology. The authors’ analyses of these interrelated aspects of the communication process enable them to provide an outline of the morphology of the community of education researchers and to raise reflectivity about the social conditions that control education research.

Author ranking based on personalized PageRank

Abstract In this paper we evaluate citation networks of authors, publications and journals, constructed from the ISI Web of Science database (Computer Science categories). Our aim was to find a method with which to rank authors of scientific papers so that the most important occupy the top positions. We utilized a hand-made list of authors, each of whom have received an ACM Fellowship or have been awarded by an ACM SIG ( Artificial Intelligence or Hardware categories). The developed method also included the adoption of the PageRank algorithm, which can be considered a measure of prestige, as well as other measures of significance (h-index, publication count, citation count, publication's author count), with these measures analyzed regarding their influence on the final rankings. Our main objective, to determine whether a better author ranking can be obtained using journal values, was achieved. The best of our author ranking systems was obtained by using journal impact values in PageRank, which was applied to a citation network of publications. The effectiveness of the ranking system was confirmed after calculations were carried out involving authors who were awarded after the final year used in our dataset or who were awarded in selected categories.

Assortative mixing, preferential attachment, and triadic closure: A longitudinal study of tie-generative mechanisms in journal citation networks

Abstract This study reveals the roles of three tie-generative mechanisms, namely, assortative mixing, preferential attachment, and triadic closure, in forming citation links in journals through the exponential random graph modeling approach. The study also adopts a longitudinal design to examine how the roles of the three mechanisms evolve over time. The data involve citation exchanges in Internet research among 680 journals in 12 subject areas from 2000 to 2013. Assortative mixing by discipline and publication foci is a significant tie-generative mechanism in journal citation networks. The magnitude of assortative mixing by discipline remains stable over time, whereas that by publication foci declines over time. Journals in Internet research demonstrate an increasing preference for influential journals to form citation links over time. The indegree of journals does not exert a significant impact on citation link formation among journals, whereas the outdegree of journals imposes a significantly negative impact on citation link formation among journals. Triadic closure is an important force that facilitates the formation of citation links among journals. The findings of this study improve our knowledge of the organizing principles that underlie journal citation networks and advance our understanding of the production process of scientific knowledge in Internet research.

Uncovering the multidisciplinary nature of technology management: journal citation network analysis

Technology management (TM) is multidisciplinary in nature. This paper investigates the multidisciplinary characteristics of TM through journal citation network analysis. The TM network composed of ten TM specialty journals and relevant journals of other disciplines is constructed based on their citation relationships. In particular, the relatedness index is employed to capture the citation relationships between journals with consideration of different journal sizes. Scrutinizing the network reveals what disciplines have contributed to TM and to what disciplines TM has contributed. The role of TM journals in exchanging knowledge with other disciplines is also identified by using brokerage analysis. TM is shown to have a high degree of interaction with six disciplines: Business and Management, Marketing, Economics, Planning and Development, Information Science, and Industrial Engineering and Operations Research. It is shown that visualizing and analyzing the TM network can provide an excellent overview of its multidisciplinary structure in terms of knowledge flow. This can help TM researchers easily grasp the historical development and fundamental features of TM.

Network closure, brokerage, and structural influence of journals: a longitudinal study of journal citation network in Internet research (2000–2010)

The study aims to assess journals' structural influence in Internet research and uncover the impacts of network structures on journals' structural influence drawing on theories of network closure and structural holes. The data of the study are the citation exchanges among 1,210 journals in and other seven social scientific fields (i.e., Business, Education, Information Science, Political Science, Psychology, and Sociology) in Internet research. The top two most influential journals in Internet research are American Economic Review and Journal of Personality and Social Psychology. Journals in Communication field emerge to be an important source of influence in Internet research, whose mean structural influence ranks third among the eight fields, below Business and Economics/Finance, but above other five fields. Journals' structural influences are found to grow over time and the growth rates vary across journals. Network brokerage is found to exert a significant impact on journals' structural influence, while the impact of network closure on journals' structural influences is not significant. The impact of network brokerage on journals' structural influence will increase over time.

Time-aware PageRank for bibliographic networks

In the past, recursive algorithms, such as PageRank originally conceived for the Web, have been successfully used to rank nodes in the citation networks of papers, authors, or journals. They have proved to determine prestige and not popularity, unlike citation counts. However, bibliographic networks, in contrast to the Web, have some specific features that enable the assigning of different weights to citations, thus adding more information to the process of finding prominence. For example, a citation between two authors may be weighed according to whether and when those two authors collaborated with each other, which is information that can be found in the co-authorship network. In this study, we define a couple of PageRank modifications that weigh citations between authors differently based on the information from the co-authorship graph. In addition, we put emphasis on the time of publications and citations. We test our algorithms on the Web of Science data of computer science journal articles and determine the most prominent computer scientists in the 10-year period of 1996–2005. Besides a correlation analysis, we also compare our rankings to the lists of ACM A. M. Turing Award and ACM SIGMOD E. F. Codd Innovations Award winners and find the new time-aware methods to outperform standard PageRank and its time-unaware weighted variants.