• Title/Summary/Keyword: 인용분석

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A Review of the Development and Critique of Citation Analysis (인용분석의 발전과 그에 대한 비판)

  • Jung, Kyung-Hee
    • Journal of Information Management
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    • v.30 no.2
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    • pp.53-68
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    • 1999
  • This paper focuses on the critique of citation analysis and then attempts to prospect for the future. The development of citation analysis has been marked by the invention of new techniques and measures, the exploitation of new tools, and the needs of evaluation of scientific research. Normative theory takes the lead in this development. But critics have questioned both the assumptions and methods of citation analysis. This critics are based on the microsociological perspective.

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The Citation Analysis as a Research Method for Sociology of Knowledge (지식사회학의 연구방법으로서 인용분석)

  • Lee Soo-Sang
    • Journal of Korean Library and Information Science Society
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    • v.30 no.2
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    • pp.155-178
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    • 1999
  • Ciatation analysis is a information analysis method based on the phenomenon of citing previous documents in the source document. There are many well-known studies exploring citation analysis and it applications. This paper does not attempt to review this extensive area of applications, but to demonstrate the sociological aspect of citation analysis. Specifically, this paper have reviewed the citation analysis as a quantitative method for the studies of sociology of knowledge. For this, I have described various basic methods such as citation behavior, citation count, impact factor, citation relationship etc. And I have classified into four applied areas of sociology of knowledge; (1) flow of knowledge resources, (2) evaluation of knowledge resources, (3) evaluation of knowledge community, and (4) utilization in terms of knowledge policy. Finally, I have clarified the some limitations and shortcomings of citation analysis that have addressed by citation and citation analysis itself.

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Multi-faceted Citation Analysis for Quality Assessment of Scholarly Publications (학술논문 품질평가를 위한 다방면 인용분석방식)

  • Yang, Ki-Duk;Meho, Lokman
    • Journal of the Korean Society for information Management
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    • v.28 no.2
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    • pp.79-96
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    • 2011
  • Despite the widespread use, critics claim that citation analysis has serious limitations in evaluating the research performance of scholars. First, conventional citation analysis methods yield one-dimensional and sometimes misleading evaluation as a result of not taking into account differences in citation quality, not filtering out citation noise such as self-citations, and not considering non-numeric aspects of citations such as language, culture, and time. Second, the citation database coverage of today is disjoint and incomplete, which can result in conflicting quality assessment outcomes across different data sources. This paper discuss the findings from a citation analysis study that measured the impact of scholarly publications based on the data mined from Web of Science, Scopus, and Google Scholar, and briefly describes a work-in-progress prototype system called CiteSearch, which is designed to overcome the weaknesses of existing citation analysis methods with a robust citation-based quality assessment approach.

Ego-centered Topic Citation Analysis on Folksonomy Research Documents (폭소노미 연구 문헌에 대한 자아 중심 주제 인용 분석)

  • Lee, Jae Yun
    • Journal of the Korean Society for information Management
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    • v.29 no.4
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    • pp.295-312
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    • 2012
  • This research aims to present the ego-centered topic citation analysis, which is a new application of White's ego-centered citation analysis, for analyzing multilayered knowledge structure of a subject domain. An experimental topic citation analysis was carried out on the folksonomy research documents retrieved from Web of Science. Ego-centered topic citation analyses on folksonomy research domain were conducted in three stages: ego-documents set analysis, topic citation identity analysis, and topic citation image analysis. The results showed that the ego-centered topic citation analysis suggested in this study was successfully performed to illustrate the inner and the outer knowledge structures of folksonomy research domain.

Domain Analysis on Economics by Utilizing Cocitation Analysis of Multiple Authorship (복수저자기반 동시인용분석을 활용한 지적구조 분석: 경제학 분야를 중심으로)

  • Kwak, Sun-Young;Chung, Eun-Kyung
    • Journal of the Korean Society for information Management
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    • v.29 no.1
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    • pp.115-134
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    • 2012
  • The author co-citation analysis is generally based on the frequency of the first author because most citation databases include only the first author in the bibliographic information. In this sense, the purpose of this study is to provide a better knowledge structure by utilizing the multiple authorship of author co-citation analysis. To achieve the purpose of this study, four different data sets are prepared: (1) counting the first author, (2) counting all the author without limiting the total frequency, (3) counting all the author with limiting the total frequency, and (4) counting adjusted frequencies based on the order of author subscription. The findings of this study show that there are clear differences between the knowledge structure counting all the author and the one counting only the first author. In addition, depending on the different methods, there are subtle changes of cluster members for authors.

Analyzing folksonomy research documents with ego centered citation analysis (자아 중심 인용 분석을 응용한 폭소노미 연구 문헌 분석)

  • Lee, Jae Yun
    • Proceedings of the Korean Society for Information Management Conference
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    • 2012.08a
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    • pp.153-156
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    • 2012
  • White가 제안한 자아 중심 인용 분석은 연구자를 대상으로 다면적인 분석을 가능하게 하는 방법이다. 이 연구에서는 자아 중심 인용 분석을 연구자 단위가 아닌 연구 주제에 대한 분석으로 응용하는 자아 중심 주제 인용 분석 기법을 제안하고, 시험적으로 폭소노미 주제의 연구문헌 집단에 응용하여 관련 연구의 핵심 문헌들과 주요 적용 이론을 반영하는 인용 정체성과 인용 이미지를 파악해보았다.

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Review of Author Name Disambiguation Techniques for Citation Analysis (인용분석에서의 모호한 저자명 식별을 위한 방법들에 관한 고찰)

  • Kim, Hyun-Jung
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.23 no.3
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    • pp.5-17
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    • 2012
  • In citation analysis, author names are often used as the unit of analysis and some authors are indexed under the same name in bibliographic databases where the citation counts are obtained from. There are many techniques for author name disambiguation, using supervised, unsupervised, or semisupervised learning algorithms. Unsupervised approach uses machine learning algorithms to extract necessary bibliographic information from large-scale databases and digital libraries, while supervised approaches use manually built training datasets for clustering author groups for combining them with learning algorithms for author name disambiguation. The study examines various techniques for author name disambiguation in the hope for finding an aid to improve the precision of citation counts in citation analysis, as well as for better results in information retrieval.