University of Illinois Urbana-Champaign

Topic-based author cocitation analysis: A preliminary exploration

Bu, Yi; Huang, Win-bin; Ding, Ying; Ai, Peng

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https://hdl.handle.net/2142/96700

Description

Title
Topic-based author cocitation analysis: A preliminary exploration
Author(s)
  • Bu, Yi
  • Huang, Win-bin
  • Ding, Ying
  • Ai, Peng
Issue Date
2017
Keyword(s)
  • Author cocitation analysis
  • Topic modeling
  • Cocitation analysis
  • Citation analysis
  • Bibliometrics
Abstract
Author cocitation analysis (ACA) plays a significant role in mapping knowledge domains. However, it has been criticized to be relatively less informative because topic- and semantic-level information of citations has seldom been integrated into ACA. This poster aims to improve the traditional ACA by combining topical information of cocited authors with author cocited counts, which is called topic-based ACA. Author-Conference-Topic (ACT) model is adopted in this research to calculate topic distributions of authors. Compared with traditional ACA, topic-based ACA shows a better clustering ability in visualization and mines more details in knowledge domain mappings.
Publisher
iSchools
Series/Report Name or Number
iConference 2017 Proceedings
Type of Resource
text
Language
en
Permalink
http://hdl.handle.net/2142/96700
Copyright and License Information
Copyright 2017 Yi Bu, Win-bin Huang, Ying Ding, and Peng Ai

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