FLE: A Fuzzy Logic Algorithm for Classification of Emotions in Literary Corpora

Luis-Gil Moreno-Jiménez, Juan-Manuel Torres-Moreno, Juan-Manuel Torres-Moreno, Hanifa Boucheneb, Roseli Wedemann


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.


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