Intellectual Structure of Knowledge in Information Retrieval: A Co-Word Analysis

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Bigdeloo Esmaeil

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Journal Paper

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Journal: Scientometrics Research Journal Year:2023 | Volume: | Issue: Page(s): 269-296

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Title

Intellectual Structure of Knowledge in Information Retrieval: A Co-Word Analysis

Author(s)

Bigdeloo Esmaeil | Issue Writer Certificate

Keywords

Information RetrievalQ4

LISTA DatabaseQ4

Co-word AnalysisQ4

Clustering AnalysisQ4

Abstract

Purpose: This study aims to analyze the intellectual structure of knowledge in Information Retrieval based on Co-word Analysis. Nowadays, the field of Information Retrieval has primarily shifted from information science to computer science. In information science, Information Retrieval refers to the interaction between individuals, and the Information Retrieval system refers to making judgments related to the results obtained from the selection of search strategies. While in computer science, Information Retrieval is the extraction of relevant information that meets user needs from a large amount of unstructured information stored in a computer. Co-word Analysis is a method of content analysis that is obtained through the co-occurrence of words or concepts in texts and sources, and through which the main concepts of a scientific field or field, and through this knowledge, conceptual patterns and events, scientific structure, conceptual network, hierarchical relations of concepts, and conceptual categories of that field can be discovered, drawn, and managed. Co-word Analysis is a tool for discovering hidden patterns and emerging conceptual events. Methodology: As an applied bibliometrics study, the research uses Co-word Analysis and clustering techniques. The research data consists of Information Retrieval of 13490 articles which were indexed in the Library, Information Science & Technology Abstracts (LISTA) database during 1967-2018. RavarpreMAP, bibExcel, SPSS, and VOSviewer were used for analysis. Findings: The results showed that during 1967-2018, the trend of publishing articles in the first two decades was steady. However, in the following two decades, there was a pattern of fluctuation, with occasional declines and rises. The Journal of the American Society for Information Science & Technology published 687 articles and has made the greatest contribution to research publication in this field. The publications in Information Processing & Management and Journal of the American Society for Information Science are ranked second and third, with 667 and 637 articles, respectively. The most frequently mentioned keyword in the text is "information storage and retrieval system, " which appears 3652 times. Other frequently mentioned topics include the World Wide Web, information resource management, information science, information services, search engines, websites, and the search for electronic information resources. These topics ranked second to tenth in terms of frequency and attention. Additionally, there is a strong co-occurrence between the following pairs: website-World Wide Web, Internet-World Wide Web, and information resource management-information storage and retrieval system. The use of hierarchical clustering by the Ward method resulted in the creation of 13 subject clusters, including computer network and multimedia systems,academic library and access to information,database and Information Retrieval,search strategy,data mining cluster and database,online library catalog,tutorials and web versions 1, 2, and 3,catalog and subject heading,Madeline,ontology and machine learning,library and information technology services,information organization and knowledge management,and artificial intelligence and medical informatics. Conclusion: The results showed that recent developments in information storage and retrieval systems, as well as users' need for quick access to up-to-date and sufficient information, have led to changes in the subject areas of Information Retrieval. These changes include the transformation of traditional libraries into virtual, digital, and automated libraries, the evolution of the one-dimensional web to the interactive web or Web2, and the management of electronic resources, databases, digital libraries, ontology, data mining, social networks, machine learning, natural language processing, knowledge management, and artificial intelligence. Information Retrieval is now widely used in various fields such as medicine, social networking, image recovery, music, and more. The field of Information Retrieval is a multidisciplinary field and has extensive connections with other fields. The results of cluster analysis, illustration, and examination of high-frequency topics clearly demonstrate this relationship.

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