Dataset Information

Detecting and analyzing research communities in longitudinal scientific networks.

ABSTRACT: A growing body of evidence shows that collaborative teams and communities tend to produce the highest-impact scientific work. This paper proposes a new method to (1) Identify collaborative communities in longitudinal scientific networks, and (2) Evaluate the impact of specific research institutes, services or policies on the interdisciplinary collaboration between these communities. First, we apply community-detection algorithms to cross-sectional scientific collaboration networks and analyze different types of co-membership in the resulting subgroups over time. This analysis summarizes large amounts of longitudinal network data to extract sets of research communities whose members have consistently collaborated or shared collaborators over time. Second, we construct networks of cross-community interactions and estimate Exponential Random Graph Models to predict the formation of interdisciplinary collaborations between different communities. The method is applied to longitudinal data on publication and grant collaborations at the University of Florida. Results show that similar institutional affiliation, spatial proximity, transitivity effects, and use of the same research services predict higher degree of interdisciplinary collaboration between research communities. Our application also illustrates how the identification of research communities in longitudinal data and the analysis of cross-community network formation can be used to measure the growth of interdisciplinary team science at a research university, and to evaluate its association with research policies, services or institutes.

SUBMITTER: Leone Sciabolazza V

PROVIDER: S-EPMC5552257 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Detecting and analyzing research communities in longitudinal scientific networks.

Leone Sciabolazza Valerio V Vacca Raffaele R Kennelly Okraku Therese T McCarty Christopher C

PloS one 20170810 8

A growing body of evidence shows that collaborative teams and communities tend to produce the highest-impact scientific work. This paper proposes a new method to (1) Identify collaborative communities in longitudinal scientific networks, and (2) Evaluate the impact of specific research institutes, services or policies on the interdisciplinary collaboration between these communities. First, we apply community-detection algorithms to cross-sectional scientific collaboration networks and analyze di ...[more]

PMID: 28797047

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Project description:In recent decades, we have observed an intensification of science, technology and innovation activities in Brazil. The increase in production of scientific papers indexed in international databases, however, has not been accompanied by an equivalent increase in the impact of publications. This paper presents a methodology for analyzing production and the impact of certain research areas in Brazil related to two aspects: the origin of the journals (national or foreign) and international collaboration. These two variables were selected for being of particular importance in understanding the context of scientific production and communication in countries with emerging economies. The sample consisted of papers written by Brazilian researchers in 19 subfields of knowledge published from 2002 to 2011, totaling 85,082 papers. To calculate the impact, we adopted a normalized indicator called the relative subfield citedness (Rw) using a window of 5 years to obtain measurements evaluated in 2 different years: 2007 and 2012. The data on papers and citations were collected from the Web of Science database. From the results, we note that most of the subfields have presented, from one quinquennium to another, improved performance in the world production rankings. Regarding publication in national and foreign journals, we observed a trend in the distribution maintenance of production of the subfields based on the origin of the journal. Specifically, for impact, we identified a lower Rw pattern for Brazilian papers when they were published in national journals in all subfields. When Brazilian products are published in foreign journals, we observed a higher impact for those papers, even surpassing the average global impact in some subfields. For international collaboration, we analyzed the percentage of participation of foreign researchers and the connection between collaboration and the impact of papers, especially emphasizing the distinction of hyperauthorship papers in terms of production and impact.

Dataset Information

Detecting and analyzing research communities in longitudinal scientific networks.

Publications

Detecting and analyzing research communities in longitudinal scientific networks.

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