Complexities and nuances of online book reviews in scholarly research
Hu, Yuerong
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https://hdl.handle.net/2142/124648
Description
Title
Complexities and nuances of online book reviews in scholarly research
Author(s)
Hu, Yuerong
Issue Date
2024-04-08
Director of Research (if dissertation) or Advisor (if thesis)
Downie, John Stephen
Doctoral Committee Chair(s)
Downie, John Stephen
Committee Member(s)
Underwood, Ted
Diesner, Jana
LeBlanc, Zoe
Department of Study
Information Sciences
Discipline
Information Sciences
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Digital Humanities
User-generated Content
Book Reviews
Data Quality
Critical Data Science
Language
eng
Abstract
In the last two decades, the abundance of online book reviews has opened up unprecedented research opportunities for scholars who are interested in empirically studying the interaction between readers and books, particularly in digital humanities (DH). However, limitations and challenges have emerged from existing scholarly conceptualization and usage of such datasets in DH. In particular, the real-world complexities and nuances associated with online book reviews have been under-investigated, which poses questions about the scholarly usability of such datasets and the significance of research findings. To address these gaps, this dissertation conducts three case studies on online book ratings, ranked book lists, and textual reviews collected from Douban and Goodreads (two large online book review platforms based in China and the U.S. respectively). The case studies empirically illuminate three under-examined aspects of online book reviews: transiency, cultural dependency, and user participation dynamics. The findings of this dissertation (1) empirically reveal the real-world complexities and under-investigated features of online book reviews and their impacts on scholarly research; and, (2) demonstrate practical methods for examining and improving the scholarly usability and interpretability of such datasets for more contextualized and critical research on online book reviews
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