Issues in the analysis of co-authorship networks

Abstract

Scientific collaboration is a complex phenomenon that improves the sharing of competences and the production of new scientific knowledge. Social Network Analysis is often used to describe the scientific collaboration patterns defined by co-authorship relationships. Different phases of the analysis of collaboration are related to: data collection, network boundary setting, relational data matrix definition, data analysis and interpretation of results. The aim of this paper is to point out some issues that arise in these different phases, highlighting: (i) the use of local archives versus international bibliographic databases; (ii) the use of different approaches for setting boundaries in a whole-network; (iii) the definition of a co-authorship data matrix (binary and weighted ties) and (iv) the analysis and the interpretation of network measures for co-authorship data. We discuss the different choices that can be made in these phases within an illustrative example on real data which is referred to scientific collaboration among researchers affiliated to an academic institution. In particular, we compare global and actor-level network measures computed from binary and weighted co-authorship networks in different disciplines

Collaboration experiences across scientific disciplines and cohorts

“…In previous studies, the key variables measuring the social dynamics of research collaboration have focused on collaboration experiences (e.g., Youtie and Bozeman 2014), ethical problems in research co-authoring (e.g., Marušić et al 2011), and variations in co-authorship network (De Stefano et al 2011;Liu et al 2005;Uddin et al 2013). In line with these earlier studies, we believe that negative collaboration experiences across scientific disciplines and cohorts represent a key dimension of the social dynamics of research collaboration that is not well addressed in previous research.…”

“…For example, mathematicians traditionally focused on producing single-authored papers, but they are more willing to published coauthored papers in recent years (Brunson et al 2014;Genest and Thibault 2001;Newman 2004). Social sciences and humanities fields, which typically have lower co-authorship rates than the natural sciences, have also demonstrated an increase in co-authorship patterns over time (Cronin et al 2003;De Stefano et al 2011;Endersby 1996;Larivière et al 2006;Lewis et al 2012;Moody 2004;Ossenblok et al 2014;Wuchty et al 2007). For example, Web of Science data shows that the percentage of single-authored papers in the social sciences has dropped from 72 percent in 1981 to just 38 percent in 2012.…”

Scientific collaboration dynamics in a national scientific system

“…In earlier bibliometric approaches, several studies focused on co-authorship in the social or natural sciences, but very few included comparisons between different scientific disciplines (De Stefano et al. 2011). Scientific disciplines still represent a crucial institutional and organizational framework within which scientific activities take place.…”

(Not So) Dangerous Liaisons: A Framework for Evaluating Collaborative Research Projects

“…Encouraging collaboration between various disciplines results in the sharing of domain-specific knowledge, but also in the emergence of new knowledge (De Stefano, Giordano, & Vitale, 2011), thus providing novel solutions for unresolved age-old problems. Yet, what entails "successful" interdisciplinary collaboration has largely remained unclear (Huutoniemi et al, 2010).…”