Macro-level collaboration network analysis and visualization with Essential Science Indicators: A case of social science

Abstract

Cross-national collaboration has been shaped by internationalization of scientific relationships. To study the synergic network of high quality research patterns, this paper collects a total of 300 top 50 items, in each indicator from the big database, Essential Science Indicators, which lists top-ranking papers, scientists and institutions from 2005 to 2015. First, the country level relations of co-authorship addresses in five indicator variables are extracted in the field of social sciences to build international collaboration networks. The social network analysis (SNA) method was applied to calculate the metrics of vertices, edges, average degree, average shortest path, diameter, clustering coefficient and betweenness centrality to illuminate the structural characters and collaboration patterns. Based on the international collaboration similarities, this paper also visualizes the endemic clustering groups of six networks, as cluster dendrograms, using Hierarchical Clustering (HC) method. Findings illustrate that USA, England and Canada are outstanding countries in the international collaboration networks of five indicators. There are geographical groups in European countries in the collaboration networks of scientists, institutes and countries/territories. It is also found that international collaboration contributes to both highly cited papers in the recent 10 years and hot papers in the recent 2 years in this field, rather than geographical similarity does. Those conclusions are critical for policy makers to produce guidelines on how to encourage researchers to build collaboration networks with high-level scholars in different countries