Comparative analysis of classics book review data created by users across Douban and Goodreads

Abstract While empirical research on online book reviews has advanced our understanding of book reception and everyday reading, more cross-platform and comparative analyses are needed to cross-examine and enrich existing perspectives on these topics. This paper presents our comparative analysis of user-created reviews of “classics” across two platforms: Goodreads based in the U.S., and Douban based in China. With book tagging, rating, and reviewing data collected from the two platforms, we examined how 144 classics identified by users on Goodreads and 141 classics on Douban were characterized and received across platforms. Our analysis reveals how book reviewers’ interests in and opinions about classics differ across platforms and demonstrates the necessity of gaining a more comprehensive understanding of classics. We also contribute a parallel dataset of classics across Goodreads and Douban for future investigations. To the best of our knowledge, this is the first parallel classics dataset across Anglophone and non-Anglophone platforms. In addition, we identify three primary challenges in aligning and comparing cross-platform data regarding metadata quality, rating systems, and multi-lingual data processing. We present these challenges and discuss how we managed to overcome them. Our case study furthers existing conversations on the characterization and reception of classics online and informs future cross-platform online book review studies.