A. Sadabadi, S. Ramezani, K. Fartash, and Iman Nikijoo
{"title":"Mapping and Analyzing the Scientific Map of Knowledge Organization Using Research Indexed in the WOS Database","authors":"A. Sadabadi, S. Ramezani, K. Fartash, and Iman Nikijoo","doi":"10.5771/0943-7444-2022-6-448","DOIUrl":null,"url":null,"abstract":"Scientometrics has found many applications in describing, explaining and predicting the scientific status of researchers, educational and research groups, universities, organizations and countries in various national and international arenas. By studying the scientific products of different countries, their status in the production of science can be evaluated. Present study was conducted using a scientometrics approach and using co-word analysis and social network analysis (SNA) to investigate relationships in the field of knowledge organization. In this regard, research indexed in web of science on the topic of “knowledge organization” has been analyzed using software including VOSviewer, Gephi, Publish or Perish. The findings of the study show that the most frequently used topics and words are knowledge organization and classification. Also, the most valuable subject areas were identified based on the maps drawn using the closeness and centrality of indexes, taxonomy, ontology and knowledge organization systems. Co-authorship analysis revealed that the co-authorship network is discrete and has low-density, with a total of 12,491 citations in all articles. Also, the most prolific author is Hjorland, followed by Smiraglia and Dahlberg. using the co-word map of knowledge organization, policymakers can plan appropriately through the knowledge of the research and thematic status of knowledge organization.","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":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Knowledge Organization","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.5771/0943-7444-2022-6-448","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: 0
Abstract
Scientometrics has found many applications in describing, explaining and predicting the scientific status of researchers, educational and research groups, universities, organizations and countries in various national and international arenas. By studying the scientific products of different countries, their status in the production of science can be evaluated. Present study was conducted using a scientometrics approach and using co-word analysis and social network analysis (SNA) to investigate relationships in the field of knowledge organization. In this regard, research indexed in web of science on the topic of “knowledge organization” has been analyzed using software including VOSviewer, Gephi, Publish or Perish. The findings of the study show that the most frequently used topics and words are knowledge organization and classification. Also, the most valuable subject areas were identified based on the maps drawn using the closeness and centrality of indexes, taxonomy, ontology and knowledge organization systems. Co-authorship analysis revealed that the co-authorship network is discrete and has low-density, with a total of 12,491 citations in all articles. Also, the most prolific author is Hjorland, followed by Smiraglia and Dahlberg. using the co-word map of knowledge organization, policymakers can plan appropriately through the knowledge of the research and thematic status of knowledge organization.
科学计量学在描述、解释和预测研究人员、教育和研究团体、大学、组织和国家在各个国家和国际领域的科学地位方面已经发现了许多应用。通过研究不同国家的科学产品,可以评价其在科学生产中的地位。本研究采用科学计量学方法,运用共词分析和社会网络分析(SNA)对知识组织领域的关系进行了研究。在此基础上,利用VOSviewer、Gephi、Publish or Perish等软件对web of science中收录的关于“知识组织”主题的研究进行分析。研究结果表明,学生使用频率最高的话题和词汇是知识组织和分类。利用索引、分类法、本体和知识组织系统的紧密性和中心性绘制地图,确定了最有价值的主题领域。合作作者分析表明,合作作者网络是离散的、低密度的,所有文章共被引用12491次。此外,最多产的作家是荷兰,其次是斯米拉格利亚和达尔伯格。利用知识组织共词图,决策者可以通过知识组织的研究知识和专题地位进行适当的规划。