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Title:A Multi-Aspect Topical Analysis of User-Generated Content
Author(s):Choi, Yunseon
Subject(s):Online reviews
User-generated content
Social networking sites
Text analysis
Abstract:As analyzing and understanding users’ online reviews has increasingly become an essential part of the business decision, there has been sufficient research on online reviews about products and services. However, there have been few studies done on the usefulness of online book reviews for understanding users’ interests in discussing books. This study is part of a larger research project that aims to investigate whether online reviews on children’s books would represent significant factors in selecting books for children. This study extends our previous research on the topical analysis of online reviews on Goodreads.com. In this study, we aim to identify users’ interests in discussing books by analyzing the frequency of words that users used in their book reviews. This study also examines whether the patterns of word frequency would help understand the features of books. The findings of this study contribute to identifying multiaspect topics of a book that users are concerned about in reviewing the book. This study has implications for providing practical insights into the intrinsic values of users’ book reviews at the social networking site.
Issue Date:2020-10-13
Series/Report:Data Mining
Natural Language Processing
Classification
Metadata
Genre:Conference Poster
Type:Text
URI:http://hdl.handle.net/2142/108786
Date Available in IDEALS:2020-10-09


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