Sentiment Analysis on Covid-19 Tweets

This is a project to analyze the sentiment of tweets about Covid-19. The project is done in Python using gabrielpreda dataset. The dataset contains 14,000 tweets about Covid-19. The dataset is available on Kaggle here. The dataset is also available on Github. The dataset contains the following columns:

• user_name: The name of the user
• user_location: The location of the user
• user_description: The description of the user
• user_created: The date the user created their account
• user_followers: The number of followers the user has
• user_friends: The number of friends the user has
• user_favourites: The number of tweets the user has liked in the account
• user_verified: Whether the user is verified or not
• date: The date the tweet was created
• text: The text of the tweet
• hashtags: The hashtags in the tweet
• source: The app used to post the tweet
• is_retweet: Whether the tweet is a retweet or not

Libraries Used

• Pandas
• Numpy
• Matplotlib
• Seaborn
• Plotly
• String
• Collections
• NLTK
• Sklearn
• Re

Data Cleaning

• Removing the rows with missing values
• Removing the rows with duplicate values
• Removing the rows with retweets
• Removing the rows with tweets that are not in English

LICENSE

MIT License