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In the world of technology, one of the best communication mediums is via text, audio, video, etc. The Internet has changed how people from all over the globe communicate with each other. People from all over the globe share their views on various social media content by liking, disliking, and commenting. The enormous amount of data in the form of comments on various social media platforms needs to be analyzed. The paper focuses on emotion detection using comments from one of the widely used platforms – YouTube. The comments are extracted from YouTube using a Python program and YouTube API and further analyzed using the three machine learning models, i.e., “Logistic Regression”, “Support Vector Machine (SVM)”, and “Random Forest”.

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Understanding Viewer Emotions Through Text Analysis: A Machine Learning Perspective

  • 会议论文

  • 发表日期：

    2026年

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  • Anand Kumar,
  • Rashmi Agrawal

摘要

In the world of technology, one of the best communication mediums is via text, audio, video, etc. The Internet has changed how people from all over the globe communicate with each other. People from all over the globe share their views on various social media content by liking, disliking, and commenting. The enormous amount of data in the form of comments on various social media platforms needs to be analyzed. The paper focuses on emotion detection using comments from one of the widely used platforms – YouTube. The comments are extracted from YouTube using a Python program and YouTube API and further analyzed using the three machine learning models, i.e., “Logistic Regression”, “Support Vector Machine (SVM)”, and “Random Forest”.