Deep Affective Meaning Sentiment Analysis (DAMSA): Towards Emotion-Aware Text Understanding

Sentiment analysis traditionally classifies text as positive, negative, or neutral, often overlooking deeper human emotions and context. This work introduces Deep Affective Meaning Sentiment Analysis (DAMSA), a framework designed to capture both surface-level sentiment and deeper affective states in text. DAMSA integrates lexicon-based sentiment scoring with deep learning models, including recurrent neural networks and transformers, to enhance emotion-aware text understanding. Potential applications include education, healthcare, social media monitoring, and customer feedback analysis. This study bridges computational linguistics and affective psychology to enable a more holistic interpretation of textual data.