Twitter Sentiment Analysis Lab

Dataset (tweets.csv)

The dataset contains approximately 2000 different (scrapped) tweets with the following attributes:

• 'id' : unique 19 digit id for each tweet
• 'created_at' : date & time of each tweet (or retweet)
• 'text' : tweet details/ description
• 'location' : origin of tweet

Objective

• Sentiment label - for each tweet based on it's text, devise a method to assign an appropriate sentiment ('positive', 'negative' or 'neutral'). This is achieved by using TextBlob (https://textblob.readthedocs.io/en/dev/)
• Text Analytics/NLP - to extract features from tweet texts
• Machine Learning - Building a robust & optimized ML model to accurately predict the sentiment associated with each tweet & explanation of the built model