Web Application for Sentiment Analysis of Thai Viewers on YouTube
Keywords:
Sentiment Analysis, Thai Word Segmentation, Social Media, YouTubeAbstract
This research presents the development and application of sentiment analysis techniques for Thai-language comments on YouTube, using a dataset categorized into three types of sentiment: positive, negative, and neutral. The research begins with text preparation and preprocessing, such as Thai word segmentation and removing stopwords to clean the data. Text modeling techniques and the VADER tool were employed to analyze the sentiment of the comments. After processing, a Word Cloud was generated to visualize frequently occurring words in positive and negative sentiment comments, along with graphs depicting the sentiment distribution within the dataset. The analysis results reveal patterns of sentiment distribution across various comments, which can be utilized to study online user behavior. Besides, data from a trending video featuring a pygmy hippopotamus named "Moo Deng" was used as a case study.
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