Is Self-Citation Biased? An Investigation via the Lens of Citation Polarity, Density, and Location

Lina Zhou (), Uchechukwuka Amadi () and Dongsong Zhang ()
Additional contact information
Lina Zhou: The University of North Carolina at Charlotte
Uchechukwuka Amadi: Northcentral University
Dongsong Zhang: The University of North Carolina at Charlotte

Information Systems Frontiers, 2020, vol. 22, issue 1, No 9, 77-90

Abstract: Abstract Traditional citation analysis methods have been criticized because their theoretical base of statistical counts does not reflect the motive or judgment of citing authors. In particular, self-citations may give undue credits to a cited article or mislead scientific development. This research aims to answer the question of whether self-citation is biased by probing into the motives and context of citations. It takes an integrated and fine-grained view of self-citations by examining them via multiple lenses — polarity, density, and location of citations. In addition, it explores potential moderating effects of citation level and associations among location contexts of citations to the same references for the first time. We analyzed academic publications across different topics and disciplines using both qualitative and quantitative methods. The results provide evidence that self-citations are free of bias in terms of citation density and polarity uncertainty, but they can be biased with respect to positivity and negativity of citations. Furthermore, this study reveals impacts of self-citing behavior on some citation patterns involving citation density, location concentration, and associations. The examination of self-citing behavior from those new perspectives shed new lights on the nature and function of self-citing behavior.

Keywords: Citation analysis; Self-citation; Bias; Polarity; Density; Location (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s10796-018-9889-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:infosf:v:22:y:2020:i:1:d:10.1007_s10796-018-9889-9

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10796

DOI: 10.1007/s10796-018-9889-9

Access Statistics for this article

Information Systems Frontiers is currently edited by Ram Ramesh and Raghav Rao

More articles in Information Systems Frontiers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().