Sentiment Analysis of Tweets for Indian Election Using Random Forest Classifier
Keywords:Sentiment Analysis, Hyperparameter, Classification, Machine Learning, Indian Election
Now a day, a huge number of user opinions are posted on every social media by thousands of users for any events, topic, current news, etc. Twitter is one of the biggest social media where people can post their tweets, share, and discuss it. Sentiment analysis is a study of people’s feeling, reviews represented in textual form. The election is one of the most popular topic on social media. User’s feeling or review on a related election is improving the national democratic process of elections. The research work proposed machine learning-based classifier for classifying the Indian election-related tweets (Positive or Negative). We proposed hyperparameter tuned random forest classification which used the efficient feature to classify Indian election-related tweets. In this work, we compared the result with other different technique result in the comparison random forest technique gives the more accurate result. Our research aim is analysed user sentiments about the Indian election using random forest classifier.