While several studies have suggested that implicit semantic communities can be identified within user generated content, the majority have focused on identifying these communities via networks of "tags" within folksonomies. This method can be problematic due to the lack of linguistic context inherent in tags as collections of discrete terms. This study attempted a different approach to this problem by analyzing a corpus of user generated reviews for popular science books taken from Amazon. It searched the reviews for patterns of shared core semantic meanings as constituted by syntagmatic relations between "topic" and "comment." Preliminary results showed that (1) core semantic meanings expressed via "topic" and "comment" relations were salient across reviews for a given book and across books within the genre and (2) specific patterns of core semantic meanings suggested the presence of different user communities constituted through similar manners of commenting on the books. The results provide insight into the social ways that readers accumulate shared meaning around books through repetition, interpretation, annotation.

This study will investigate the potential of user generated book reviews (UGBRs) to illustrate how readers' opinions about a book's appeal are contextualized within personal and social attitudes toward reading. It will employ an expanded concept of-appeal‖ from readers' advisory literature that moves from a narrow focus on-book appeal‖ to a focus on-reading appeal,‖ or how a reader's personal and social contexts affect their reading processes, motives, and justifications for reading. C.S. Peirce's approach to semiotics is employed both as a means of illuminating the reading process and as an analytical framework. Preliminary results suggest that UGBRs might be useful to readers' advisory services by both providing insight into the different sorts of appeal that reading holds to readers and by demonstrating how this reading appeal is constituted within different subgroups .