Abstract
Years of Technological progress have made machines capable of understanding basic human emotions from their tonality. Written text is also an important method of communication where a wide range of emotions can be expressed. Thus, it is imperative for machines to be also able to understand the emotions being portrayed in the text messages. For this study, an analysis was done on a dataset known as GoEmotions for the potential development of a chatbot. This dataset contains 58 thousand selected Reddit comments collected from various subreddits that use the English language. The results shows that, these were then classified and categorized based on the principal preserved component analysis (PPCA) method into four main emotions; positive, negative, ambiguous, and neutral successfully. And for this task, Natural Language Processing (NLP) pre-training was applied, which was a transformer based machine learning technique.
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Rahat, F.R. et al. (2022). Data Analysis Using NLP to Sense Human Emotions Through Chatbot. In: Singh, M., Tyagi, V., Gupta, P.K., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2022. Communications in Computer and Information Science, vol 1614. Springer, Cham. https://doi.org/10.1007/978-3-031-12641-3_6
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