Co-authorship and Co-occurrence Network Structure Analysis of Iranian Researchers on Quality of Life Using Social Networks Analysis

The purpose is to analyze the structure of social network Co-occurrence and Co-authorship in quality of life using social network analysis indicators in the Clarivate analytics WoS database.

This research is a scientometric study and has been done using co-occurrence and co-authorship analysis. Social network analysis (SNA) was used to obtain an understanding of the nodes on quality of life areas. MESH subject heading was used to extract related terms on quality of life. The population included 1421 documents which were extracted from Clarivate analytics WoS from 2000 to 2017. Descriptive statistics and Scientometric methods have been used to analyze the data.

The results showed that among researchers, Montazeri has been the most prolific author with 97 documents. Among the Institutions, Tehran University of Medical Sciences with 831 documents ranked first. The total documents for the year 2014 were 284 documents, the area in this research was internal and general medicine with 235 documents, and among documents, the highest type of documents was related to articles with 1111 records. In the study of co-occurrence network in the field of quality of life, 9 thematic clusters were identified: Motor Control (109), Obesity (54), Lifestyle (53), Meta-analysis (52), Risk factors (39), Women (33), Risk (20), Eating (13) and Coronary disease (13). The Motion Control cluster is the largest cluster, accounting for 84% of the total network volume.

The results of the co-occurrence analysis show that this area consists of 9 clusters, the top three clusters were Motor Control, Obesity, and Lifestyle.  Analysis of centrality indicators shows that most of the top-ranking authors are mainly working at the top universities of the country, and the top authors are mostly concentrated on the universities located in the capital rather than the other cities. Also, the study of macro indicators of co-authorship network shows that this structure is considered as a Small-world network due to its average short path length (2.77), network diameter equal to 5, and relatively high clustering coefficient (3.75).