Content-based author co-citation analysis

Yoo Kyung Jeong, Min Song, Ying Ding

Research output: Contribution to journalArticle

58 Citations (Scopus)

Abstract

Author co-citation analysis (ACA) has long been used as an effective method for identifying the intellectual structure of a research domain, but it relies on simple co-citation counting, which does not take the citation content into consideration. The present study proposes a new method for measuring the similarity between co-cited authors by considering author's citation content. We collected the full-text journal articles in the information science domain and extracted the citing sentences to calculate their similarity distances. We compared our method with traditional ACA and found out that our approach, while displaying a similar intellectual structure for the information science domain as the other baseline methods, also provides more details about the sub-disciplines in the domain than with traditional ACA.

Original languageEnglish
Pages (from-to)197-211
Number of pages15
JournalJournal of Informetrics
Volume8
Issue number1
DOIs
Publication statusPublished - 2014 Jan 1

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Information science
information science

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Library and Information Sciences

Cite this

Jeong, Yoo Kyung ; Song, Min ; Ding, Ying. / Content-based author co-citation analysis. In: Journal of Informetrics. 2014 ; Vol. 8, No. 1. pp. 197-211.
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Content-based author co-citation analysis. / Jeong, Yoo Kyung; Song, Min; Ding, Ying.

In: Journal of Informetrics, Vol. 8, No. 1, 01.01.2014, p. 197-211.

Research output: Contribution to journalArticle

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