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

Publication Title

Journal of Informetrics

Divisions

MathematicalSciences,aei

Volume

15

Issue

3

Publisher

Elsevier

Publisher Location

RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS

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