Abstract

With the increasing popularity of social media, online reviews have become one of the primary information sources for book selection. Prior studies have analyzed online reviews, mostly in the domain of business. However, little research has examined the content of online book reviews of children’s books. Book reviews generated by book readers contain different aspects of information, such as opinions, feedback, or emotional responses, from the perspectives of readers. This study explores what aspects of the books are addressed in readers’ reviews, and then it intends to identify categorical features or facets of online book reviews of children’s books. We employed a textual analysis approach including the latent Dirichlet allocation topic modeling to analyze the content of book reviews. The results indicate that online book reviews exhibit different facets of the books, which can be used as access points by potential readers to help them select relevant books.

Document Type

Article

Publication Date

7-2020

Notes/Citation Information

Published in The Library Quarterly, v. 90, no. 3.

© 2020 by The University of Chicago. All rights reserved.

The copyright holder has granted the permission to post this article here.

Digital Object Identifier (DOI)

https://doi.org/10.1086/708962

Available for download on Thursday, July 01, 2021

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