Literature DB >> 25046832

Associating co-authorship patterns with publications in high-impact journals.

Michael E Bales1, Daniel C Dine2, Jacqueline A Merrill3, Stephen B Johnson4, Suzanne Bakken5, Chunhua Weng6.   

Abstract

OBJECTIVES: To develop a method for investigating co-authorship patterns and author team characteristics associated with the publications in high-impact journals through the integration of public MEDLINE data and institutional scientific profile data.
METHODS: For all current researchers at Columbia University Medical Center, we extracted their publications from MEDLINE authored between years 2007 and 2011 and associated journal impact factors, along with author academic ranks and departmental affiliations obtained from Columbia University Scientific Profiles (CUSP). Chi-square tests were performed on co-authorship patterns, with Bonferroni correction for multiple comparisons, to identify team composition characteristics associated with publication impact factors. We also developed co-authorship networks for the 25 most prolific departments between years 2002 and 2011 and counted the internal and external authors, inter-connectivity, and centrality of each department.
RESULTS: Papers with at least one author from a basic science department are significantly more likely to appear in high-impact journals than papers authored by those from clinical departments alone. Inclusion of at least one professor on the author list is strongly associated with publication in high-impact journals, as is inclusion of at least one research scientist. Departmental and disciplinary differences in the ratios of within- to outside-department collaboration and overall network cohesion are also observed.
CONCLUSIONS: Enrichment of co-authorship patterns with author scientific profiles helps uncover associations between author team characteristics and appearance in high-impact journals. These results may offer implications for mentoring junior biomedical researchers to publish on high-impact journals, as well as for evaluating academic progress across disciplines in modern academic medical centers.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Co-authorship patterns; Evaluation; Journal impact factor; MEDLINE; Social networking

Mesh:

Year:  2014        PMID: 25046832      PMCID: PMC4260991          DOI: 10.1016/j.jbi.2014.07.015

Source DB:  PubMed          Journal:  J Biomed Inform        ISSN: 1532-0464            Impact factor:   6.317


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