BEET-M Quadrant-Mapped Verbs: A Fuzzy and binary Dataset of 9,000 English Verbs for Emotional and Behavioral Influence Modeling

This dataset presents a curated collection of 9,000 English verbs annotated with normalized fuzzy values across four cognitive-behavioral quadrants of the BEET-M (Behavior Engagement Emotion Trigger Modes) model: Value & Credibility (NW), Relationship & Human Impact (NE), Process & Information (SE), and Time Urgency (SW). Each verb is assigned fuzzy scores summing to 1.0, along with a corresponding binary vector marking its dominant influence quadrant. This dataset supports applications in affective computing, persuasive communication, human-computer interaction, and natural language processing, particularly for emotionally adaptive systems and context-aware word scoring.