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Mining author relationship in scholarly networks based on tripartite citation analysis.

ABSTRACT: Following scholars in Scientometrics as examples, we develop five author relationship networks, namely, co-authorship, author co-citation (AC), author bibliographic coupling (ABC), author direct citation (ADC), and author keyword coupling (AKC). The time frame of data sets is divided into two periods: before 2011 (i.e., T1) and after 2011 (i.e., T2). Through quadratic assignment procedure analysis, we found that some authors have ABC or AC relationships (i.e., potential communication relationship, PCR) but do not have actual collaborations or direct citations (i.e., actual communication relationship, ACR) among them. In addition, we noticed that PCR and AKC are highly correlated and that the old PCR and the new ACR are correlated and consistent. Such facts indicate that PCR tends to produce academic exchanges based on similar themes, and ABC bears more advantages in predicting potential relations. Based on tripartite citation analysis, including AC, ABC, and ADC, we also present an author-relation mining process. Such process can be used to detect deep and potential author relationships. We analyze the prediction capacity by comparing between the T1 and T2 periods, which demonstrate that relation mining can be complementary in identifying authors based on similar themes and discovering more potential collaborations and academic communities.

SUBMITTER: Wang F

PROVIDER: S-EPMC5678701 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Mining author relationship in scholarly networks based on tripartite citation analysis.

Wang Feifei F Wang Xiaohan X Yang Siluo S

PloS one 20171108 11

Following scholars in Scientometrics as examples, we develop five author relationship networks, namely, co-authorship, author co-citation (AC), author bibliographic coupling (ABC), author direct citation (ADC), and author keyword coupling (AKC). The time frame of data sets is divided into two periods: before 2011 (i.e., T1) and after 2011 (i.e., T2). Through quadratic assignment procedure analysis, we found that some authors have ABC or AC relationships (i.e., potential communication relationshi ...[more]

PMID: 29117198

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Project description:BackgroundIt has been argued that science and society are in the midst of a far-reaching renegotiation of the social contract between science and society, with society becoming a far more active partner in the creation of knowledge. On the one hand, new forms of knowledge production are emerging, and on the other, both science and society are experiencing a rapid acceleration in new forms of knowledge utilization. Concomitantly since the Second World War, the science underpinning the knowledge utilization field has had exponential growth. Few in-depth examinations of this field exist, and no comprehensive analyses have used bibliometric methods.MethodsUsing bibliometric analysis, specifically first author co-citation analysis, our group undertook a domain analysis of the knowledge utilization field, tracing its historical development between 1945 and 2004. Our purposes were to map the historical development of knowledge utilization as a field, and to identify the changing intellectual structure of its scientific domains. We analyzed more than 5,000 articles using citation data drawn from the Web of Science. Search terms were combinations of knowledge, research, evidence, guidelines, ideas, science, innovation, technology, information theory and use, utilization, and uptake.ResultsWe provide an overview of the intellectual structure and how it changed over six decades. The field does not become large enough to represent with a co-citation map until the mid-1960s. Our findings demonstrate vigorous growth from the mid-1960s through 2004, as well as the emergence of specialized domains reflecting distinct collectives of intellectual activity and thought. Until the mid-1980s, the major domains were focused on innovation diffusion, technology transfer, and knowledge utilization. Beginning slowly in the mid-1980s and then growing rapidly, a fourth scientific domain, evidence-based medicine, emerged. The field is dominated in all decades by one individual, Everett Rogers, and by one paradigm, innovation diffusion.ConclusionWe conclude that the received view that social science disciplines are in a state where no accepted set of principles or theories guide research (i.e., that they are pre-paradigmatic) could not be supported for this field. Second, we document the emergence of a new domain within the knowledge utilization field, evidence-based medicine. Third, we conclude that Everett Rogers was the dominant figure in the field and, until the emergence of evidence-based medicine, his representation of the general diffusion model was the dominant paradigm in the field.

Dataset Information

Mining author relationship in scholarly networks based on tripartite citation analysis.

Publications

Mining author relationship in scholarly networks based on tripartite citation analysis.

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