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Sentiment analysis of comments, the user can get to know about the community acceptance of its channel/video based on that one can maintain their content quality.

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IshtyM/Sediment-Analysis-of-You-Tube-Comments

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Sediment-Analysis-of-You-Tube-Comments

Sentiment Analysis is one of the Natural Language Processing techniques, which can be used to determine the sensibility behind the texts, i.e. tweets, movie reviews, youtube comments, any incoming message, etc. With the help of this sentiment analysis of comments, the user can get to know about the community acceptance of its channel/video based on that one can maintain their content quality. Csv file of GB Comments is used for the comments of you tube. Initially, data pre-processing is done. In this, comments having minimum and maximum likes are separated in two lists, which is used for comparison, Then, TextBlob library is used to determine the positive and negative polarity of comments which is followed by formation of wordcloud. Collection library is used to count the most common word occurrence.

Libraries Used:

Pandas, Numpy, Matplotlib, TextBlob Library, Wordloud, Collections

Programing Language

Python

IDE Used

Jupyter Notebook

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Sentiment analysis of comments, the user can get to know about the community acceptance of its channel/video based on that one can maintain their content quality.

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