Mitra Zarei - Information Sciences Department, International University of Imam Reza, Mashhad, Iran
Mahmoud Salari - Information Sciences Department, International University of Imam Reza, Mashhad, Iran
Zahra Jafarzadeh - Information Sciences Department, International University of Imam Reza, Mashhad, Iran

Background: Structural holes as a considerable issue in network approach can be tracked in central indices.Objectives: This research aims to survey indices that can measure structural holes.We are looking for the most important scientificauthors and their connections in the field of medical genetics to facilitate information flow in the network of medical geneticsrelations.Methods: First, co-authorship network of Iranian medical genetics scientists (faculty members) was extracted via searching Scopus,Web of Science, and PubMed databases, as a result of which ۷۴۵۱ articles were retrieved. With co-authorship techniques, the mostcentral nodes in the network were picked as highlighted scientists. In the next phase, two other indices (i.e., hypertext inducedtopics search [HITS] and PageRank) were calculated with the help of Sci۲ and compared to redundancy, efficiency and effective sizeas structural hole indices.Results: There was a significant relationship between the two groups of indices. There were few structural holes in our networkbecause redundancy and constraint were low. Constraint index and centrality indices can be used for extracting structural holes.Conclusions: In confirmation of previous studies, the constraint index can be used as a method for extracting structural holes.Compared to the HITS algorithm, the constraint index works best in this regard. At the same time, the study of HITS and PageRankindicators showed a significant association between the figures derived from the calculation of these two indicators, and each onecan be employed to find structural holes.

Structural Holes, Co-authorship, Social Network Analysis, Centrality Measures, HITS Algorithm, PageRank Algorithm,Genetics, Medical