Global scientific collaboration: A social network analysis and data mining of the co-authorship networks

Abstract

Co-authorship networks consist of nodes and numerous links indicating scientific collaboration of researchers. These networks could be studied through social networks analysis and data mining techniques. The focus of the article is twofold: the first objective is the analysis of the co-authorship networks of the top 60 countries that had the highest number of scientific publications in the world, and the second one is the discovery of collaboration patterns of highly cited papers of these countries. To do so, all scientific publications of the top 60 countries in all fields as well as their highly cited papers were included in the study period between 2011 and 2015. The research samples in the first part included 10,460,999 documents and in the second part encompassed 711,025 highly cited papers. Required data were extracted from web of science database. To analyse co-authorship networks, centrality indices and clustering coefficient were used. UCINET, Pajek, VOSviewer and BibExcel software were used to map co-authorship networks of the countries and to calculate indices. Finally, the discovery of collaboration patterns in highly cited papers is studied through association rules. The research data indicated that over 95% of documents has been produced by the top 60 countries. In addition, the USA, Germany, England, France and Spain launched the most co-authorship. Quantitatively, there have been the most powerful collaboration links between China and the USA, the USA and England, the USA and Germany, and the USA and Canada. The clustering data indicated that collaborations of the top countries of the world were in three main clusters. The Friedman test showed that there was a significant difference in the priorities of the countries for collaboration; and the USA, China, England, Germany, France, Japan and Italy are in the top priority for collaboration, respectively. The results of collaboration pattern in highly cited papers indicated that the USA participates in more than half of collaboration patterns for producing highly cited papers.

Research topic flows in co-authorship networks

“…These co-authorship networks are a special case of scientific collaboration networks (Moed et al, 2004) and are a constant subject of research, in particular with respect to scientometric analysis. State of the art studies investigate these networks in a global scope (Isfandyari-Moghaddam et al, 2021), focusing on whole research areas (Ji et al, 2022) or incorporate temporal aspects (Ji et al, 2022).…”

Scientific collaboration and thematic analysis of the tourism industry in the context of COVID-19: a bibliometric approach

“…We observe that Hall C. Michael, Gössling Stefan and Scott Daniel, the most cited authors with 800, 782 and 765 citations, respectively, also possess the leading positions according to the scores of degree centrality and eigenvector centrality. These results indicate their prominent position in terms of scientific collaboration, but also their influential role, prestigious and status within the scientific network (Isfandyari-Moghaddam et al , 2021). Betweenness centrality ranks Baum Tom in the first position – demonstrating that he represents a channel between several authors, increasing his power and decreasing his dependence on others (Koseoglu et al , 2018).…”

“…Finally, we calculated the degree of density of different clusters from the keyword co-occurrence map. It appears that nodes in the cluster that includes – tourism, hospitality industry, crisis management and corporate social responsibility – hold closer connections with each other (density = 20.1677), compared with nodes in other clusters (Isfandyari-Moghaddam et al , 2021).…”

“…Crisis management and risk perceptions also prove to be central and influential according to their high ranks in all three centrality measures (Muritala et al , 2020). We find less influenced topics and fields like destination (destination image), sustainable tourism (sustainable development), overtourism, air transport, corporate social responsibility, etc., with relative low influences and ties of connections with main nodes from the map, due to their smaller values of betweenness and eigenvector centrality (Isfandyari-Moghaddam et al , 2021). These topics may be highlighted as underexplored areas and future research would be necessary to investigate in breadth and depth.…”

A Scientometric Visualization Analysis for Molecular Mechanisms of Substance Abuse and Its Neurotoxicity From 1997 to 2021

“…Considering its global harm, there has been a significant increased hot topic research and collaborative projects in countries, such as the United States, Germany, and Canada (Fujáková-Lipski et al, 2017;Costa et al, 2021;Sogos et al, 2021). Based on legalized marijuana policies in the United States and Canada, similar domestic and international situations and potential cooperative opportunities increased exponentially; additionally, the United States provides attractive financial grants to facilitate efficient cooperation and productivity (Goundar et al, 2021;Isfandyari-Moghaddam et al, 2021). Under a shared global concern of drug abuse, worldwide scientific cooperation should be further strengthened to highlight research quality, and the outcomes should be noted to more deeply illustrate the harm of substance abuse and drug-induced toxicity (Rahim et al, 2012).…”