Notice bibliographique
- Notice
000 cam 22 3 450
001 FRBNF47052406000000X
010 .. $a 1009270397
010 .. $a 9781009270397 $z 9781009270403 $b ebook $z 9781009270380 $b PDF ebook
035 .. $a OCoLC1304813199
100 .. $a 20221025d2022 m y0engy50 ba
101 0. $a eng
102 .. $a GB
105 .. $a a z 00|y|
106 .. $a z
181 .0 $6 01 $a i $b xxxe
181 .. $6 02 $c txt $2 rdacontent
182 .0 $6 01 $a n
182 .. $6 02 $c n $2 rdamedia
200 1. $a The shapes of stories $b Texte imprimé $e sentiment analysis for narrative $f Katherine Elkins, ...
214 .0 $a Cambridge $c Cambridge university press $d 2022
215 .. $a 115 pages $c illustrations $d 23 cm
225 |. $a Cambridge elements $i Elements in digital literary studies $x 2633-4380
300 .. $a Includes bibliographical references (p. [110]-115)
330 .. $a 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
410 .0 $0 47124820 $t Elements in digital literary studies (Print) $x 2633-4380 $d 2022
676 .. $a 801.950 285 $v 23
801 .3 $a US $b OCoLC $c 20221025 $h 1304813199 $2 marc21
801 .0 $b YDX $g rda
930 .. $5 FR-751131010:47052406001001 $a 2022-169858 $b 759999999 $c Tolbiac - Rez de Jardin - Littérature et art - Magasin $d O
