Complexities associated with user-generated book reviews in digital libraries: temporal, cultural, and political case studies

While digital libraries (DL) have made large-scale collections of digitized books increasingly available to researchers [31, 67], there remains a dearth of similar data provisions or infrastructure for computational studies of the consumption and reception of books. In the last two decades, user-generated book reviews on social media have opened up unprecedented research possibilities for humanities and social sciences (HSS) scholars who are interested in book reception. However, limitations and gaps have emerged from existing DH research which utilize social media data for answering HSS questions. To shed light on the under-investigated features of user-generated book reviews and the challenges they might pose to scholarly research, we conducted three exemplar cases studies: (1) a longitudinal analysis for profiling the temporal changes of ratings and popularity of 552 books across ten years; (2) a cross-cultural comparison of book ratings of the same 538 books across two platforms; and, (3) a classification experiment on 20,000 sponsored and non-sponsored books reviews. Correspondingly, our research reveals the real-world complexities and under-investigated features of user-generated book reviews in three dimensions: the transience of book ratings and popularity (temporal dimension), the cross-cultural differences in reading interests and book reception (cultural dimension), and the user power dynamics behind the publicly accessible reviews ("political" dimension). Our case studies also demonstrate the challenges posed by user-generated book reviews' real-world complexities to their scholarly usage and propose solutions to these challenges. We conclude that DL stakeholders and scholars working with user-generated book reviews should look into these under-investigated features and real-world challenges to evaluate and improve the scholarly usability and interpretability of their data.