Network effects on scientific collaborations

• Published in: PloS one Vol. 8; no. 2; p. e57546
• Main Authors: Uddin, Shahadat, Hossain, Liaquat, Rasmussen, Kim
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 28.02.2013; Public Library of Science (PLoS)
• Subjects: Authoring; Citation analysis; Citations; Collaboration; Communication; Cooperation; Cooperative Behavior; Data analysis; Data processing; Documents; Identification methods; Impact analysis; Information science; International co authorship; Journal Impact Factor; Mathematicians; Network analysis; Networks; Organization theory; Regression analysis; Researchers; Science; Science Policy; Scientific papers; Scientists; Scientometrics; Social and Behavioral Sciences; Social network analysis; Social networks; Social organization; Societies, Scientific - organization & administration; Society; Statistical analysis; Steel; Steel structures; Strength; Studies
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0057546

The analysis of co-authorship network aims at exploring the impact of network structure on the outcome of scientific collaborations and research publications. However, little is known about what network properties are associated with authors who have increased number of joint publications and are being cited highly. Measures of social network analysis, for example network centrality and tie strength, have been utilized extensively in current co-authorship literature to explore different behavioural patterns of co-authorship networks. Using three SNA measures (i.e., degree centrality, closeness centrality and betweenness centrality), we explore scientific collaboration networks to understand factors influencing performance (i.e., citation count) and formation (tie strength between authors) of such networks. A citation count is the number of times an article is cited by other articles. We use co-authorship dataset of the research field of 'steel structure' for the year 2005 to 2009. To measure the strength of scientific collaboration between two authors, we consider the number of articles co-authored by them. In this study, we examine how citation count of a scientific publication is influenced by different centrality measures of its co-author(s) in a co-authorship network. We further analyze the impact of the network positions of authors on the strength of their scientific collaborations. We use both correlation and regression methods for data analysis leading to statistical validation. We identify that citation count of a research article is positively correlated with the degree centrality and betweenness centrality values of its co-author(s). Also, we reveal that degree centrality and betweenness centrality values of authors in a co-authorship network are positively correlated with the strength of their scientific collaborations. Authors' network positions in co-authorship networks influence the performance (i.e., citation count) and formation (i.e., tie strength) of scientific collaborations.