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Showing 2 results for Co-Word Analysis

Faramarz Sohaili, Ali Shaban, Aliakbar Khase,
Volume 2, Issue 4 (3-2016)
Abstract

Background and Aim: The intellectual structure of knowledge and its research front can be identified by co-word analysis. This research attempts to reveal the intellectual structure of knowledge in information behavior inquiries, via co-word, network analysis, and science visualization tools.

Methods: Bibliometric methodology and social network analysis are used. Population comprises 2146 records in the field of Information Behavior during 2006-2014, which had been retrieved from Web of Science.

Results: finding indicate that “Information Retrieval” is the most frequent keyword in the Information Behavior inquiries. Also, “Information Needs and Information Behavior” are the most frequent co-occurred keywords. Use of hierarchical cluster analysis by Ward method led to the creation of 11 topical clusters in Information Behavior, including among others: “User Studies,”  “Health Information Behavior,” and “Social Networks.”

Conclusions: The results indicated that the co-word analysis can be well uncover the intellectual structure of scientific disciplines. The results of the strategic diagram showed that “health information behavior”, “user studies”, “social networks”, and “relevance in information retrieval” are among well-matured and central clusters with pivotal role. Moreover, four clusters, including “information resources”, “Web search”, “information retrieval”, and “information management” are among emerging or declining clusters. Finally, although the “interface and information technology” cluster is in the central part, but it is underdeveloped. Due to the frequency of keywords on the one hand, and clusters obtained on the other hand, it seems to be a close relationship between information behavior and health studies. Therefore, it seem that many of information behavior studies have been conducted in health and medical communities


Mohamad Hassanzadeh, Somaye Ahmadi, Fatemeh Zandian,
Volume 5, Issue 1 (6-2018)
Abstract

Purpose: This study aims to reveal the intellectual structure of Knowledge and Information Science and its evolution along with the review of journals subjective scope based on 6830 abstract in the ten core journal in the JCR 2013, over the ten years (2004-2013).
Methodology: In this research, co-word and Correspondence analysis of 150 words -selected by tf-idf weight- were done after parametric analysis. To this end, the Cosine theta index and the second-order affinity were used for the hierarchical clustering based on the average-linkage algorithm.
Findings: The results of the co-word analysis reveal 3 mature clusters and 1 immature cluster in relation to the second cluster. Furthermore, the study of journals' domain show four clusters and the time progress show two clusters in counterclockwise motion.
Conclusion: In general, the results show except cluster four all clusters have a stable state with conceptual maturity, and along with constant concepts, a conceptual metamorphosis can be seen under the influence of technological change.
 

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