Content- and proximity-based author co-citation analysis using citation sentences

Ha Jin Kim, Yoo Kyung Jeong, Min Song

Research output: Contribution to journalArticlepeer-review

48 Citations (Scopus)


Author co-citation analysis (ACA) has been widely used for identifying the subject disciplines of authors. Citations can reveal the explicit relationship between authors as well as their subject research fields. However, previous studies have seldom considered citation contents that convey useful implicit information on the authors or the influence of the links between the authors’ subject fields by taking citation locations into account. This study aims to reveal the implicit relationship in the authors’ subject disciplines by considering both citation contents and proximity. To this end, the researchers propose a new ACA method, called content- and proximity-based author co-citation analysis (CPACA). For the study, we extracted citation sentences and locations from full-text articles in the oncology field. The top 15 journals on oncology in Journal Citation Reports were selected, and 6,360 full-text articles from PubMed Central were collected. The results show that the proposed method enables the identification of distinct sub-fields of authors to represent authors’ subject relatedness.

Original languageEnglish
Pages (from-to)954-966
Number of pages13
JournalJournal of Informetrics
Issue number4
Publication statusPublished - 2016 Nov 1

Bibliographical note

Funding Information:
This work was supported by the Bio-Synergy Research Project ( NRF-2013M3A9C4078138 ) of the Ministry of Science, ICT and Future Planning through the National Research Foundation and (in part) by the Yonsei University Future-leading Research Initiative of 2015 ( 2015-22-0119 ).

Publisher Copyright:
© 2016 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Library and Information Sciences


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