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Affective taxomonies of the reading experience: Using user‐generated reviews for readers' advisory
Author(s) -
Spiteri Louise F.,
Pecoskie Jen
Publication year - 2016
Publication title -
proceedings of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.193
H-Index - 14
ISSN - 2373-9231
DOI - 10.1002/pra2.2016.14505301032
Subject(s) - reading (process) , context (archaeology) , selection (genetic algorithm) , affect (linguistics) , inclusion (mineral) , computer science , psychology , content (measure theory) , world wide web , information retrieval , linguistics , social psychology , history , artificial intelligence , communication , mathematics , philosophy , archaeology , mathematical analysis
This paper examines affect in the reading experience to help both readers' advisors and readers as they work to suggest books to readers and choose books for their individual context. Using Grounded Theory analysis of 536 user‐generated reviews from 831 bibliographic records of a selection of fiction titles (n=22) in Canadian public libraries whose catalogues allow for the inclusion of user content were analyzed for affective content. The content of the reviews was coded into three categories, Emotions, Tones, and Associations and taxonomies were developed. Emotions are represented by 9 basic categories, and 44 unique emotions, Tones by 11 basic categories and 141 unique tones, and Associations by 7 basic categories and 31 unique associations. Affective access points can serve as an important addition to the bibliographic records for works of fiction and it is suggested that the derived taxonomies could be used as facets by which to narrow the results of a search for readers' advisory efforts in public libraries.