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Title:Mining users’ interests in discussing books on social media
Author(s):Choi, Yunseon
Subject(s):Online review
Social discussion
Cluster analysis
Abstract:Libraries have used book reviews to support their decision on book selection and collection building. Many researchers proved that online reviews are helpful for the decision on product or service purchases. However, little research has been done on online book reviews about their usefulness in selecting children. This study conducts a frequency analysis of words applied to the categories identified based on the Latent Dirichlet Allocation topic model. For the analysis of online book reviews, this study selects sample books from the recommended reading lists from the American Library Association (ALA). It collects reviews about the books from Goodreads. This study investigates whether the patterns of word frequency would show interesting points which reflect the characteristics and features of books. This study performs a hierarchical cluster analysis on the selected books and further examined reviews by conducting a content analysis on review texts. This study’s findings will identify the aspects of a book that users are concerned about in reviewing the books. Future research will take further steps in the investigation of the relationship between the word frequency and the features of books.
Issue Date:2021-09-20
Series/Report:Social media
Metadata
Data mining
Natural language processing
Genre:Conference Poster
Type:Text
URI:http://hdl.handle.net/2142/110894
Date Available in IDEALS:2021-09-17


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