What makes a book review compelling? Analyzing informativeness, writing style, and enjoyment

Amateur book reviews published on Digital Social Reading (DSR) platforms play a crucial role in sharing reading experiences and capturing reader preferences. However, little attention has been given to the linguistic features that influence the way reading experiences are conveyed and shape readers’ perceptions of the aspects discussed in reviews. This study addresses this gap by combining Computational Stylometry and Machine Learning techniques to examine how the linguistic features of book reviews combined with the demographic characteristics of review readers impact the reception of book reviews, focusing in particular on three key aspects that might make a book review compelling, namely informativeness, writing style, and enjoyment. To this aim, we relied on a corpus of Italian Goodreads reviews to investigate how amateur reviewers communicate their reading experience and on a survey to collect human judgments about review reception. Additionally, we investigated the extent to which the review style and the demographic characteristics of review readers can predict the different aspects of review perception. Our findings revealed that linguistic characteristics play a crucial role in shaping reader perceptions and are equally or even more predictive than demographic information in automatic classification models. Nevertheless, while demographic factors such as gender and birth year offer limited utility in forming homogeneous reader groups, reading habits emerged as a relevant factor in identifying shared trends among readers. These insights contribute to a deeper understanding of reader involvement in DSR communities and offer valuable insights for both publishers and review platforms in defining book recommender systems.