Classifying emotion in Thai youtube comments
Phakhawat Sarakit, Thanaruk Theeramunkong, Choochart Haruechaiyasak, Manabu Okumura · 2015
To add more value on YouTube, a popular portal of social media clips, it is worth recognizing automatically the mood of a media clip using the comments given to such clip. This paper presents a method to classify emotion of a Thai media clip on YouTube using the comments given to the clip. Six basic emotions considered are Anger, Disgust, Fear, Happiness, Sadness and Surprise. Performances using three alternative machine learning algorithms, namely multinomial naïve Bayes (MNB), decision tree (DT) and support vector machine (SVM) are compared. As the result, SVM achieves the highest accuracy in the commercial advertisement (AD) genre with an accuracy of 76.14% while MNB with yields the best result in the music video (MV) genre with an accuracy of 84.48%.