The novel coronavirus (COVID-19) that was first reported at the end of 2019 has impacted almost every aspect of life as we know it. Ever since there are millions of people tweeting about the coronavirus outbreaks. To analyse those tweets a dataset containing tweets and the sentiments expressed by that tweet is provided for the model. The task is to train a model that can predict the sentiment of tweeter users based on their tweets. Basically, it’s a multiclass classification problem.
- Goal - Analyse the sentiments of tweeter users by processing their tweets
- Tools used - Jupyter notebook, fast API, Streamlit
- Models created - 6
- Best model - Linear Regression with count vectorizer
- Accuracy - 78 %
Tweet Example
Prediction
