Abstract
This study is part of a larger research project which aims to investigate whether online reviews on children's books would represent significant factors which are useful for selecting appropriate books for children. This paper presents the preliminary results on topic detection of online book reviews. Topic modeling using Latent Dirichlet Allocation (LDA) generated several topic terms from online reviews, and we categorized those topic terms into eleven categories. Sentiment analysis was applied to examine the emotional aspects of the reviews. We examined that sentiment words which have a powerful effect on polarity values to determine whether those sentiment words appear as topic words extracted by the LDA topic modeling. The results of our study have a significant implication on understanding user behavior in online book reviews.
Original language | English |
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Title of host publication | Proceedings - 2019 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2019 |
Editors | Maria Bonn, Dan Wu, Stephen J. Downie, Alain Martaus |
Pages | 418-419 |
Number of pages | 2 |
ISBN (Electronic) | 9781728115474 |
DOIs | |
State | Published - Jun 2019 |
Event | 19th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2019 - Urbana-Champaign, United States Duration: Jun 2 2019 → Jun 6 2019 |
Publication series
Name | Proceedings of the ACM/IEEE Joint Conference on Digital Libraries |
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Volume | 2019-June |
ISSN (Print) | 1552-5996 |
Conference
Conference | 19th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2019 |
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Country/Territory | United States |
City | Urbana-Champaign |
Period | 6/2/19 → 6/6/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Online reviews
- Sentiment analysis
- Social media
- Topic modeling
ASJC Scopus subject areas
- General Engineering