Text Emotion Detection using Machine Learning Algorithms
Vishakha Singh, M. Sharma, Anushka Shirode, Sanjay Mirchandani · 2023
Text Emotion determination is becoming more vital with every passing day as millions of text messages are released on a daily basis. In text analysis, the challenge lies in interpreting the ambiguity of human language, particularly when it comes to emotions. A study was carried out to detect the emotions classified into six categories as anger, fear, joy, love, sadness, and surprise. The algorithms, including Logistic Regression, Linear Support Vector Machine, and Random Forest were used for detecting and classifying the emotions. A comparative study of these methods was carried out by considering two features namely Term Frequency- Inverse Document Frequency and Count Vectors. The highest accuracy was obtained for the Count Vectors feature using the Logistic Regression method and the emotions in the text were classified accordingly.