We are going to study and predict the sentiment and emotions of people during this lockdown using machine learning. It is the process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer's attitude towards a particular topic is positive, negative, or neutral. We are going to obtain the dataset from twitter, feed the data into a suitable algorithm that performs the sentimental analysis. After performing the sentimental analysis, we are going to plot a sentiment map. The users will thus get an idea about the impact of this pandemic in various states. The users are given a choice to choose a state. Once the state is chosen, we give the analysis breakdown of top 3 keywords used in that state in the form of pie charts. This will give the user a better perspective of the morality prevailing in that state.
There is also another additional feature in our project, the user can give any keyword as input and we give them results like the number of tweets that has the keyword, the states that have the maximum number of tweets containing the keyword and the sentiment breakdown of that keyword. Using our model, the user can get better perspective about the major problems prevailing in our country due to the pandemic.
Demonstration video link: https://www.youtube.com/watch?v=-ABdpO1NF3w
Project report link: https://drive.google.com/file/d/1UYPDUxDpInvrYgXqf9tvMdxpgbwqEFVf/view?usp=sharing