Identifying Content Structure of “Knowledge and Information Science (KIS)” Studies Based on Co-word Analysis of Articles in “Web of Science (WoS)” Database (2009-2013)

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Abstract

This study aimed to identify and analyze the structure of “Knowledge and Information Science (KIS)” scientific articles using co-word analysis in the “Web of Science (WoS)” database. Methodology of this study was content analysis of articles. By co-word analysis of the articles, subjects and concepts of KIS were identified, using Between-Groups Linkage algorithm in clustering techniques. The study population was selected using the census sampling of 16475 journals’ articles in WoS database (2009-2013). Also, statistical analysis regression correlation was used. RaverPremap software, SPSS, and Excel were also used. Findings showed that the words “information”, “web”, “research”, “citation analysis”, “knowledge”, “library”, “journals”, and “technology” have high impact in studies. Analysis of clusters showed that articles words are divided into 13 clusters. The main subjects of clusters include “teaching and learning of KIS; information literacy”, “knowledge & information organization”, “Web resources and social networks”, “professional ethics in information science”, “informatics, communication and health information services”, “information management; information systems; knowledge management and innovation”, “indicators of informetrics and scintometrics”. Analyzing clusters’ concepts indicated emerging some other fields of science studies in KIS as a phenomenon. Given the diversity and increases of scientific capital of other disciplines in KIS scientific outputs, interdisciplinarity of KIS knowledge was increased as well. Awareness of the interdisciplinary relation of KIS with other fields enabled experts to strengthen the cooperation with their researchers.

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