Content-based author co-citation analysis
Yoo Kyung Jeong,
Min Song and
Ying Ding
Journal of Informetrics, 2014, vol. 8, issue 1, 197-211
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.
Keywords: Author co-citation analysis; Citation content analysis; Bibliometrics; Information science; Citation analysis (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (40)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1751157713001107
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:8:y:2014:i:1:p:197-211
DOI: 10.1016/j.joi.2013.12.001
Access Statistics for this article
Journal of Informetrics is currently edited by Leo Egghe
More articles in Journal of Informetrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().