Connection and stratification in research collaboration: An analysis of the COLLNET network

Abstract

The co-authorship network of scientists represents a prototype of social networks. By mapping the graph containing all relevant publications of members in an international collaboration network: COLLNET, we infer the structural mechanisms that govern the topology of this social system. Structure of the network effect not only individual's collaboration pattern deeply, but knowledge flowing process profoundly. However, a single view is not enough to grasp the characters of the network in details. We have to either produce global view on the structure of the network as a whole, or make a detailed inspection of some features of individuals. In this paper, some techniques for analyzing complex networks (different approaches to identify "interesting" individuals and groups, analysis of internal structure of the main core and hierarchical clustering) and visualizations of their parts are presented on the case of COLLNET collaboration graph.

Mapping library and information science in China: a coauthorship network analysis

“…Commonly used measures are diameter, mean distance, components, clusters, etc. Micro-level metrics relate to the analysis of the individual properties of network actors, for example, actor position, actor status, and distance to others, which informs us about ''the differential constraints and opportunities facing individual actors which shape their social behavior'' (Yin et al 2006(Yin et al , p. 1600. It zooms in to capture the features of the individual nodes/actors in a network with the consideration of the topology of the network.…”

“…Newman studied and compared the coauthorship graph of arXiv, Medline, SPIRES, and NCSTRL (Newman 2001a, b) and found a number of network differences between experimental and theoretical disciplines. By mapping the graph containing all relevant publications of members in an international collaboration network COLLNET, Yin et al (2006) found that this scientific community displays many aspects of a small-world network and is vulnerable to disruption. Using the Science Citation Index (SCI) data for 1990 and 2000, Wagner and Leydesdorff (2003) found that in the 10 years between 1990 and 2000, the global network has expanded to include more nations and it has become more interconnected.…”

PageRank for ranking authors in co‐citation networks

“…measures (Liu et al, 2005;Yin, Kretschmer, Hanneman, & Liu, 2006). The centrality measures the position of each vertex in the network, and directly associates with theories in social sciences as such "weak ties" and "social capital".…”

A measure of authors’ centrality in co-authorship networks based on the distribution of collaborative relationships

“…Newman studied a variety of properties of his networks, including scientists' degree and betweenness [NEWMAN, 2001A,B]. Some studies have directly applied the degree, closeness and betweenness to co-authorship networks of different domains [YIN & AL., 2006;HOU & AL., 2008]. In addition to authors' degree, closeness, betweenness and PageRank centrality, the AuthorRank centrality of authors in the domain of digital libraries was proposed [LIU & AL., 2005].…”