A Hybrid Approach for Spanish Emotion Recognition Applying Fuzzy Semantic Processing

Emotion detection is a task in sentiment analysis that deals with the extraction and analysis of emotions in texts. Recognizing implicit emotions is one of the main challenges in keyword or lexicon-based approaches. This paper presents a hybrid emotion detection approach, which combines lexicon-based emotion-relevant feature selection with a classical learning approach to determine emotion. The proposed semantic feature selection process focuses on capturing the emotional meaning of the text by computing the semantic relationship between its content and the lexicon vocabulary using a fuzzy approach, with the goal of increasing implicit emotion recognition. The proposed solution was evaluated using AIT dataset used in SemEval-2018, obtaining better results than those obtained by other solutions reported.