Enhancing Mood Detection in Textual Analysis through Fuzzy Logic Integration

This study introduces a refined methodology for mood detection within textual corpora, leveraging the principles of fuzzy logic to transcend traditional binary sentiment analysis paradigms. By instituting trapezoidal membership functions across a spectrum of emotional states and employing a robust set of fuzzy inference rules, the proposed approach yields a granular and context-sensitive interpretation of textual moods.