{"title":"全球知识组织研究共词分析:1900-2019","authors":"O. Alipour, Faramarz Soheili, A. Khasseh","doi":"10.5771/0943-7444-2022-5-303","DOIUrl":null,"url":null,"abstract":"The study’s objective is to analyze the structure of knowledge organization studies conducted worldwide. This applied research has been conducted with a scientometrics approach using the co-word analysis. The research records consisted of all articles published in the journals of Knowledge Organization and Cataloging & Classification Quarterly and keywords related to the field of knowledge organization indexed in Web of Science from 1900 to 2019, in which 17,950 records were analyzed entirely with plain text format. The total number of keywords was 25,480, which was reduced to 12,478 keywords after modifications and removal of duplicates. Then, 115 keywords with a frequency of at least 18 were included in the final analysis, and finally, the co-word network was drawn. BibExcel, UCINET, VOSviewer, and SPSS software were used to draw matrices, analyze co-word networks, and draw dendrograms. Furthermore, strategic diagrams were drawn using Excel software. The keywords “information retrieval,” “classification,” and “ontology” are among the most frequently used keywords in knowledge organization articles. Findings revealed that “Ontology*Semantic Web”, “Digital Library*Information Retrieval” and “Indexing*Information Retrieval” are highly frequent co-word pairs, respectively. The results of hierarchical clustering indicated that the global research on knowledge organization consists of eight main thematic clusters; the largest is specified for the topic of “classification, indexing, and information retrieval.” The smallest clusters deal with the topics of “data processing” and “theoretical concepts of information and knowledge organization” respectively. Cluster 1 (cataloging standards and knowledge organization) has the highest density, while Cluster 5 (classification, indexing, and information retrieval) has the highest centrality. According to the findings of this research, the keyword “information retrieval” has played a significant role in knowledge organization studies, both as a keyword and co-word pair. In the co-word section, there is a type of related or general topic relationship between co-word pairs. Results indicated that information retrieval is one of the main topics in knowledge organization, while the theoretical concepts of knowledge organization have been neglected. In general, the co-word structure of knowledge organization research indicates the multiplicity of global concepts and topics studied in this field globally.","PeriodicalId":46091,"journal":{"name":"Knowledge Organization","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Co-Word Analysis of Global Research on Knowledge Organization: 1900-2019\",\"authors\":\"O. Alipour, Faramarz Soheili, A. Khasseh\",\"doi\":\"10.5771/0943-7444-2022-5-303\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The study’s objective is to analyze the structure of knowledge organization studies conducted worldwide. This applied research has been conducted with a scientometrics approach using the co-word analysis. The research records consisted of all articles published in the journals of Knowledge Organization and Cataloging & Classification Quarterly and keywords related to the field of knowledge organization indexed in Web of Science from 1900 to 2019, in which 17,950 records were analyzed entirely with plain text format. The total number of keywords was 25,480, which was reduced to 12,478 keywords after modifications and removal of duplicates. Then, 115 keywords with a frequency of at least 18 were included in the final analysis, and finally, the co-word network was drawn. BibExcel, UCINET, VOSviewer, and SPSS software were used to draw matrices, analyze co-word networks, and draw dendrograms. Furthermore, strategic diagrams were drawn using Excel software. The keywords “information retrieval,” “classification,” and “ontology” are among the most frequently used keywords in knowledge organization articles. Findings revealed that “Ontology*Semantic Web”, “Digital Library*Information Retrieval” and “Indexing*Information Retrieval” are highly frequent co-word pairs, respectively. The results of hierarchical clustering indicated that the global research on knowledge organization consists of eight main thematic clusters; the largest is specified for the topic of “classification, indexing, and information retrieval.” The smallest clusters deal with the topics of “data processing” and “theoretical concepts of information and knowledge organization” respectively. Cluster 1 (cataloging standards and knowledge organization) has the highest density, while Cluster 5 (classification, indexing, and information retrieval) has the highest centrality. According to the findings of this research, the keyword “information retrieval” has played a significant role in knowledge organization studies, both as a keyword and co-word pair. In the co-word section, there is a type of related or general topic relationship between co-word pairs. Results indicated that information retrieval is one of the main topics in knowledge organization, while the theoretical concepts of knowledge organization have been neglected. In general, the co-word structure of knowledge organization research indicates the multiplicity of global concepts and topics studied in this field globally.\",\"PeriodicalId\":46091,\"journal\":{\"name\":\"Knowledge Organization\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Knowledge Organization\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.5771/0943-7444-2022-5-303\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Knowledge Organization","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.5771/0943-7444-2022-5-303","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 1
摘要
本研究的目的是分析世界范围内知识组织研究的结构。本应用研究采用科学计量学方法,采用共词分析。研究记录包括1900 - 2019年在《知识组织》和《编目分类季刊》上发表的所有文章以及Web of Science检索的与知识组织领域相关的关键词,其中17,950条记录完全采用纯文本格式进行分析。关键词总数为25,480个,经过修改和删除重复项后减少到12,478个。然后,将频率至少为18的115个关键词纳入最终分析,最后绘制出共词网络。使用BibExcel、UCINET、VOSviewer和SPSS软件绘制矩阵,分析共词网络,绘制树形图。利用Excel软件绘制战略图。关键字“信息检索”、“分类”和“本体”是知识组织文章中最常用的关键字。结果表明,“本体*语义网”、“数字图书馆*信息检索”和“标引*信息检索”分别是高频共词对。层次聚类结果表明,全球知识组织研究主要由8个主题聚类组成;最大的是为“分类、索引和信息检索”主题指定的。最小的集群分别处理“数据处理”和“信息和知识组织的理论概念”的主题。聚类1(编目标准和知识组织)的密度最高,聚类5(分类、索引和信息检索)的中心性最高。本研究发现,关键词“信息检索”在知识组织研究中发挥了重要作用,无论是作为关键字还是共词对。在共词部分中,共词对之间存在一种相关的或一般的主题关系。结果表明,信息检索是知识组织研究的主要内容之一,而知识组织的理论概念一直被忽视。总体而言,知识组织研究的共词结构表明了该领域研究的全球概念和主题的多样性。
A Co-Word Analysis of Global Research on Knowledge Organization: 1900-2019
The study’s objective is to analyze the structure of knowledge organization studies conducted worldwide. This applied research has been conducted with a scientometrics approach using the co-word analysis. The research records consisted of all articles published in the journals of Knowledge Organization and Cataloging & Classification Quarterly and keywords related to the field of knowledge organization indexed in Web of Science from 1900 to 2019, in which 17,950 records were analyzed entirely with plain text format. The total number of keywords was 25,480, which was reduced to 12,478 keywords after modifications and removal of duplicates. Then, 115 keywords with a frequency of at least 18 were included in the final analysis, and finally, the co-word network was drawn. BibExcel, UCINET, VOSviewer, and SPSS software were used to draw matrices, analyze co-word networks, and draw dendrograms. Furthermore, strategic diagrams were drawn using Excel software. The keywords “information retrieval,” “classification,” and “ontology” are among the most frequently used keywords in knowledge organization articles. Findings revealed that “Ontology*Semantic Web”, “Digital Library*Information Retrieval” and “Indexing*Information Retrieval” are highly frequent co-word pairs, respectively. The results of hierarchical clustering indicated that the global research on knowledge organization consists of eight main thematic clusters; the largest is specified for the topic of “classification, indexing, and information retrieval.” The smallest clusters deal with the topics of “data processing” and “theoretical concepts of information and knowledge organization” respectively. Cluster 1 (cataloging standards and knowledge organization) has the highest density, while Cluster 5 (classification, indexing, and information retrieval) has the highest centrality. According to the findings of this research, the keyword “information retrieval” has played a significant role in knowledge organization studies, both as a keyword and co-word pair. In the co-word section, there is a type of related or general topic relationship between co-word pairs. Results indicated that information retrieval is one of the main topics in knowledge organization, while the theoretical concepts of knowledge organization have been neglected. In general, the co-word structure of knowledge organization research indicates the multiplicity of global concepts and topics studied in this field globally.