Scoring the resourcefulness of researchers using bibliographic coupling patterns
Document Type
Article
Publication Date
8-1-2021
Abstract
Networks constructed from citation and publication data can be mined to find top-ranking authors or papers using graph-theoretic algorithms. This article proposes an indicator called the ``follow-score `` that identifies which authors are the most resourceful to ``follow `` in terms of referencing patterns within a given body of literature. For testing purposes, we use Web of Science indexed publications under the subject category of ``Information Science & Library Science `` between the years 2008 and 2018 inclusive. Using the top-ranking follow-worthy authors, we search the study dataset for other similar researchers using cosine similarity.
Keywords
Citation analysis, Ranking, Networks, Bibliometrics, Algorithm, Author follow-score
Divisions
MathematicalSciences,aei
Publication Title
Journal of Informetrics
Volume
15
Issue
3
Publisher
Elsevier
Publisher Location
RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS