Co-authorship network analysis of Iranian medical science researchers: A social network analysis

Co-authorship networks of scientists exhibit a pattern of developing and complicated networks. The aim of the present study was to analyze the power structure in co-authorship networks of Iranian medical science researchers based on centrality measures. Social network analysis was used as the research method. The research population was all those researchers who have published articles in one of the seven journals of Iranian medical sciences indexed by ISI. Data were collected in two phases, first electronically access to the articles and second using a questioner to gather opinions of authors with centrality roles. Pearson correlation and regression were used to analyze the data. The research finding showed that a significant correlation existed between centrality scores and productivity at P= 0.001. The findings from variance regression analysis revealed that researchers’ productivity variable was determined by factors such as degree, eigenvector and beta centrality. Most important criteria for selecting research teams from opinions of researcher with high centrality Scores are: the same proficiency, having dominant teams, having a necessary knowledge, political, cultural and scientific acceptance. The results showed that co-authorship networks of Iranian medical journals had a low centrality and few connections existed among authors. In addition, authors with high centrality scores have a quick access to other authors and resources and they regarded as powerful authors.