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- W2148334513 abstract "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%." @default.
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- W2148334513 date "2015-03-01" @default.
- W2148334513 modified "2023-09-26" @default.
- W2148334513 title "Classifying emotion in Thai youtube comments" @default.
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- W2148334513 doi "https://doi.org/10.1109/ictemsys.2015.7110808" @default.
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