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.
Bibliographical noteFunding 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 ).
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Library and Information Sciences