Applying content-based similarity measure to author co-citation analysis

Jeong, Yoo Kyung; Song, Min

Permalink

https://hdl.handle.net/2142/89428 Copy

Description

Title

Applying content-based similarity measure to author co-citation analysis

Author(s)

• Jeong, Yoo Kyung
• Song, Min

Issue Date

2016-03-15

Keyword(s)

• Author Co-citation Analysis
• similarity measure
• Word2Vec
• content analysis

Abstract

This study proposed a novel author similarity measure in author co-citation analysis (ACA). Unlike other ACA studies, we used citing sentences to reflect topical relatedness of authors. In our research, we extended traditional approaches by adopting Word2Vec, one of deep learning methods, to measure author similarity. We also conducted in-depth network analysis of author maps. The results of Word2Vec-based author map revealed more specific sub-disciplines and the important authors in perspective of topical influence than traditional approach does. Our method allows for more sophisticated analysis than the traditional ACA approach by providing a more in-depth understanding and the specific structure of a discipline.

Publisher

iSchools

Series/Report Name or Number

IConference 2016 Proceedings

Type of Resource

text

Language

eng

Permalink

http://hdl.handle.net/2142/89428

DOI

https://doi.org/10.9776/16212

Copyright and License Information

Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

Owning Collections