Text-Data-Analysis

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An In-depth Analysis of YouTube text Data using various tools and Visualization.

General Information

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• It shows how to use Text-Data to gain actionable insights and patterns and what all different type of analysis we can apply according to the Problem Statements in-hand.

• Problem Statements:

1. Performing Sentiment Analysis
2. Performing Word-Cloud Analysis
3. Emoji Analysis (New and Interesting)
4. Analysing the Most liked category?
5. Is the audience engaged or not?
6. Which channels have the largest number of trending videos?
7. Does Punctuations in title_name column have any relation with views, likes, dislikes, comment_count features?

Libraries Used

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• Pandas

• Numpy

• Matplotlib

• Seaborn

• Plotly

• TextBlob

• Emoji

• Word-Cloud