Authors:
Luis-Gil Moreno-Jiménez
1
;
Juan-Manuel Torres-Moreno
2
;
1
;
Hanifa Boucheneb
2
and
Roseli S. Wedemann
3
Affiliations:
1
Laboratoire Informatique d'Avignon, Université d'Avignon, 339 Chemin des Meinajaries, 84911 Avignon, Cédex 9, France
;
2
Département de Génie Informatique et Génie Logiciel, Polytechnique Montréal, 2500, Chemin de Polytechnique Montréal, Québec, Canada
;
3
Universidade do Estado do Rio de Janeiro, Rua São Francisco Xavier 524, 20550-900, Rio de Janeiro, RJ, Brazil
Keyword(s):
Emotion Classification, Natural Language Processing, Fuzzy Logic, Literary Sentences.
Abstract:
This paper presents an algorithm based on fuzzy logic, devised to identify emotions in corpora of literary texts, called Fuzzy Logic Emotions (FLE) classifier.
This algorithm evaluates a sentence to define the class(es) of emotions to which it belongs. For this purpose, it considers three types of linguistic variables (verb, noun and adjective) with associated linguistic values used to qualify the emotion they express. A numerical value is computed for each of these terms within a sentence, based on its frequency and the inverse document frequency (TF-IDF). We have tested our FLE classifier with an evaluation protocol, using a literary corpus in Spanish specially structured for working with the automatic detection of emotions in text. We present encouraging performance results favoring our FLE classifier, when compared to other known algorithms established in the literature used for the detection of emotions in text.