Book Topic and Emotion Classification by Child Readers in a Library in Taiwan.
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| Title: | Book Topic and Emotion Classification by Child Readers in a Library in Taiwan. |
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| Authors: | Wu, Ko-Chiu (AUTHOR), Chiu, Tzu-Heng (AUTHOR), Chen, Chun-Ching (AUTHOR), Liu, Chung-Ching (AUTHOR), Hsu, Fang-Man (AUTHOR) |
| Source: | International Journal of Human-Computer Interaction. Oct2025, Vol. 41 Issue 19, p12191-12217. 27p. |
| Subjects: | Emotions, Folksonomies, Children's literature, Taiwanese people, Reading interests, Classification of books, Sentiment analysis, Libraries |
| Geographic Terms: | Taiwan |
| Abstract: | This study created a visualized folksonomy classification that integrates topic icons and emojis to help children to find books that they like in library settings. The National Library of Public Information in Taiwan commissioned a book-navigation app using the proposed classification. We recruited 35 children to use this app to search for books to read, and they recorded their feelings about these books over a twelve-week period. A statistical analysis of 1,938 system logs was performed under three themes: thematic preferences, epistemic cognition, and social communication. The implementation of thematic and emotion icons in a folksonomy topic structure appeared to successfully aid young Taiwanese readers in finding books that they wanted. Evidence of complex relationships among cultural, psychological, cognitive, and social aspects of book-finding was found, suggesting the benefits of supervised learning in the extraction of gross-fine emotions in the sentiment analysis of multiple topics. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | This study created a visualized folksonomy classification that integrates topic icons and emojis to help children to find books that they like in library settings. The National Library of Public Information in Taiwan commissioned a book-navigation app using the proposed classification. We recruited 35 children to use this app to search for books to read, and they recorded their feelings about these books over a twelve-week period. A statistical analysis of 1,938 system logs was performed under three themes: thematic preferences, epistemic cognition, and social communication. The implementation of thematic and emotion icons in a folksonomy topic structure appeared to successfully aid young Taiwanese readers in finding books that they wanted. Evidence of complex relationships among cultural, psychological, cognitive, and social aspects of book-finding was found, suggesting the benefits of supervised learning in the extraction of gross-fine emotions in the sentiment analysis of multiple topics. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 10447318 |
| DOI: | 10.1080/10447318.2025.2453609 |
