TY - BOOK ID - 101528901 TI - The shapes of stories : sentiment analysis for narrative PY - 2022 SN - 1009270400 1009270397 1009270362 1009270389 PB - Cambridge : Cambridge University Press, DB - UniCat KW - Criticism KW - Sentiment analysis. KW - Data processing. KW - Analysis, Sentiment KW - Extraction, Opinion KW - Mining, Opinion KW - Mining, Sentiment KW - Opinion extraction KW - Opinion mining KW - Sentiment mining KW - Computational linguistics KW - Data mining KW - Evaluation of literature KW - Literary criticism KW - Literature KW - Rhetoric KW - Aesthetics KW - Technique KW - Evaluation UR - https://www.unicat.be/uniCat?func=search&query=sysid:101528901 AB - Sentiment analysis has gained widespread adoption in many fields, but not-until now-in literary studies. Scholars have lacked a robust methodology that adapts the tool to the skills and questions central to literary scholars. Also lacking has been quantitative data to help the scholar choose between the many models. Which model is best for which narrative, and why? By comparing over three dozen models, including the latest Deep Learning AI, the author details how to choose the correct model-or set of models-depending on the unique affective fingerprint of a narrative. The author also demonstrates how to combine a clustered close reading of textual cruxes in order to interpret a narrative. By analyzing a diverse and cross-cultural range of texts in a series of case studies, the Element highlights new insights into the many shapes of stories. ER -