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Emotions have played an important part in many sectors, including psychology,medicine, mental health, computer science, and so on, and categorizing them hasproven extremely useful in separating one emotion from another. Emotions can beclassified using the following two methods: (1) The supervised method'sefficiency is strongly dependent on the size and domain of the data collected.A categorization established using relevant data from one domain may not workwell in another. (2) An unsupervised method that uses either domain expertiseor a knowledge base of emotion types already exists. Though this secondapproach provides a suitable and generic categorization of emotions and iscost-effective, the literature doesn't possess a publicly available knowledgebase that can be directly applied to any emotion categorization-related task.This pushes us to create a knowledge base that can be used for emotionclassification across domains, and ontology is often used for this purpose. Inthis study, we provide TONE, an emotion-based ontology that effectively createsan emotional hierarchy based on Dr. Gerrod Parrot's group of emotions. Inaddition to ontology development, we introduce a semi-automated vocabularyconstruction process to generate a detailed collection of terms for emotions ateach tier of the hierarchy. We also demonstrate automated methods forestablishing three sorts of dependencies in order to develop linkages betweendifferent emotions. Our human and automatic evaluation results show theontology's quality. Furthermore, we describe three distinct use cases thatdemonstrate the applicability of our ontology.

TONE: A 3-Tiered ONtology for Emotion analysis