The Co-word Analysis of Publications from the Information Science and Knowledge Studies Master theses

The study of scientific networks has developed as one of the most important kinds of metrics studies over the last few decades. Drawing networks of topics through the co-word analysis approach is one of the methods used to study scientific networks. The main objective of this technique is to show the development of scientific fields through the visual display of topics.
The aim of this research work is to study the scientific network of topics examined in publications from the Information Science and Knowledge Studies master theses.
For this purpose, the information of 1237 master theses was collected from the "List of LIS theses in Iranian universities" and two databases called "irandoc" and "listhesis". In addition, "magiran "and" noormags " databases were searched for articles published from theses. Out of 508 articles extracted from these theses, 1428 keywords were then extracted.
Findings: Thematic mapping of the paper's keywords by using the co-words analysis technique indicates that the topics "Internet", "Webometrics" and "Information storage and retrieval" had top ranking for the degree-centrality and betweenness indexes. In addition, the topics "Locating libraries", "Selective dissemination of information and "Education" had the highest impact on the network in terms of closeness centrality.