ASIS&T 2013 Annual Meeting 
Montréal, Québec, Canada | November 1-5, 2013

Deconstructing the Collaborative Impact: Article and Author Characteristics That Influence Citation Count

Lori Hurley, University of Illinois at Urbana-Champaign 
Andrea Ogier, University of Illinois at Urbana-Champaign  
Vetle Torvik, University of Illinois at Urbana-Champaign 

Tuesday, 8:30am


It is well known that collaborative papers tend to receive more citations than solo-authored papers. Here we try to identify the subtle factors of this collaborative effect after accounting for attributes known to be strong predictors of citation count by analyzing metadata and citation counts for co-authored papers in the biomedical domain. Article-level attributes, such as number and diversity of authors, publication date, topic, and journal, were gathered from 98,000 PubMed article records categorized with the term ‘Breast Neoplasm,’ and citation data on these was obtained from PubMed Central (PMC). Author-level attributes, such as gender, professional age, affiliation, impact, collaboration rate and productivity, were appended as article-level attributes of collaborations. A logistic regression model was built to assess the relative weights of these factors as influences on citation counts. As expected, number of co-authors, journal, and language of the paper were the strongest predictors; some of the more subtle predictors included the greatest author h-index (positively correlated) and the diversity of author h-indexes and minimum professional age with negative weights. The combinatorial effect of these observations suggests that smaller collaborations composed of early superstars – young, rapidly successful researchers with relatively high and similar h-indexes – may be at least as influential in biomedical research as larger collaborations with different demographics.