  Emotions have played an important part in many sectors, including psychology,
medicine, mental health, computer science, and so on, and categorizing them has
proven extremely useful in separating one emotion from another. Emotions can be
classified using the following two methods: (1) The supervised method's
efficiency is strongly dependent on the size and domain of the data collected.
A categorization established using relevant data from one domain may not work
well in another. (2) An unsupervised method that uses either domain expertise
or a knowledge base of emotion types already exists. Though this second
approach provides a suitable and generic categorization of emotions and is
cost-effective, the literature doesn't possess a publicly available knowledge
base that can be directly applied to any emotion categorization-related task.
This pushes us to create a knowledge base that can be used for emotion
classification across domains, and ontology is often used for this purpose. In
this study, we provide TONE, an emotion-based ontology that effectively creates
an emotional hierarchy based on Dr. Gerrod Parrot's group of emotions. In
addition to ontology development, we introduce a semi-automated vocabulary
construction process to generate a detailed collection of terms for emotions at
each tier of the hierarchy. We also demonstrate automated methods for
establishing three sorts of dependencies in order to develop linkages between
different emotions. Our human and automatic evaluation results show the
ontology's quality. Furthermore, we describe three distinct use cases that
demonstrate the applicability of our ontology.
