A Scientometric Study of the Intellectual Structure of Researchers' Publications: Acinetobacter baumannii

Background and Aim: Acinetobacter baumannii is a major cause of nosocomial infections and is considered one of the most serious health threats worldwide. Several researchers have attempted to study and report this issue to find a solution. In this regard, the observation and monitoring of topic and conceptual priorities are thus crucial. This study aimed to identify and formulate the relationship among topic research priorities of A. baumannii to accurately understand the intellectual structure concerning A. baumannii . Materials and Methods: This scientometric study is quantitative and applied, conducted by using the co-word analysis technique. A total of 10,898 records indexed at the WOSCC were retrieved and analyzed during 2002-2021, and 102 keywords out of 12,060 keywords were selected for analysis. Following the vocabulary homogenization process, the threshold was determined, and UCINET 6.528.0.0 2017, NetDraw (2017), VOSviewer 1.6.14, and SPSS-16 software were used to analyze and preprocess the data and visualize the maps. Results: The keyword 'Multidrug Resistance (MDR)' was in first place among the most frequent keywords of A. baumannii articles. The main concepts of the documents published regarding A. baumannii were obtained using the hierarchical clustering with the Ward method (6 topic clusters). The largest cluster had 27 keywords and 680 links with a centrality of 25,185 and a density of 0.969. The distribution of clusters in the strategic diagram indicated that topic clusters were located in quadrants 1 and 3, including mature and central topics and emerging or marginal topics, respectively. Conclusion: Identifying and monitoring significant topics and conceptual priorities of the A. baumannii area with scientometric techniques is an appropriate tool for determining the intellectual structure of the A. baumannii area, leading optimal and efficient decisions in officials' research financial policy. the scientific position of the topic in the form of significant and frequent topic mapping co-occurrence in the co-occurrence matrix the role of a node in the co-word network, normalized weight matrix is considered as the edge weight in co-word graph