WhatsApp is one of the most used messenger applications today with more than 2 billion users worldwide. It was found that more than 65 billion messages are sent on WhatsApp daily, so we can use WhatsApp chat for analyzing our chat with a friend, customer, or a group of people. In this project, we will analyze WhatsApp Chat Data and Sentiment using Python. We will look for the:
- Number of images/videos being sent. Images are represented by "media omitted".
- Most Media Items sent per Whatsapp user.
- Number of messages deleted after being sent.
- Who has deleted the most messages in the group.
- The Top 10 Most Talkative Persons
- On what date, most messages were being sent.
- On what time, most messages were being sent.
- The number of letters and words used by each author in each message.
- The most common number of words in a message.
- Who exactly wrote the most letters?
- The most common number of letters per message?
- When was the group most active?
- The most active hour.
- The most suitable time of day to get your message replied to.
- On what minute, most messages were being sent.
- What are the most commonly used words?
- Count all the most used emojis.
- Select 5 reviews with the highest positive sentiment polarity score.
- Select 5 reviews with the most neutral sentiment polarity score.
- Select 5 reviews with the most negative sentiment polarity score.
- Distribution of review sentiment polarity score.
Whatsapp Data: https://github.com/ArsalanKhan0608/Whatsapp-Chat-Data-and-Sentiment-Analysis-using-Python/blob/main/WhatsappChat.txt #DataScience #DataScienceBasics #DataScienceProjects #DataScienceBootCamp #DataAnalysis #PasswordAnalysis
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