• Bhargav Jayaram Moorthy
• Prof. Deepika K

Study on emotion recognition for gauging performance of supervised machine learning algorithms. The face is an index of the mind, but it is a word that really illuminates the emotions. Many emotions are hidden in subjective posts. Once recognized, these emotions serve as the knowledge base for many organizations. Many business decisions are based on these feelings. To make a decision, there is a need to identify users’ emotions. Organizations that make emotional decisions could be profitable when the emotions are correctly identified. This paper uses supervised machine learning algorithms to accurately predict the sentiment of Twitter messages. This paper also aims to compare machine learning algorithms to predict the emotion, to generate the score generated by the model, and to compare the performance of the algorithms.

classification, dataset, deep learning, emotion recognition, processing, text mining, Twitter

" Study on Emotion Recognition for Gauging Performance of Supervised Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 6, page no.124-127, June-2020, Available :http://www.jetir.org/papers/JETIR2006019.pdf

" Study on Emotion Recognition for Gauging Performance of Supervised Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 6, page no. pp124-127, June-2020, Available at : http://www.jetir.org/papers/JETIR2006019.pdf