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Title:Applying content-based similarity measure to author co-citation analysis
Author(s):Jeong, Yoo Kyung; Song, Min
Subject(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.
Issue Date:2016-03-15
Publisher:iSchools
Citation Info:NA
Series/Report:IConference 2016 Proceedings
Genre:Conference Paper / Presentation
Type:Text
Language:English
URI:http://hdl.handle.net/2142/89428
DOI:10.9776/16212
Rights Information:Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.
Date Available in IDEALS:2016-03-08


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