Sentiment Analysis on Textual Tweets using Ensemble Classifier (LSTM-GRU)

Sentiment analysis has become increasingly difficult due to the rise of social media. Product reviews, trends, and political commentary can all be found on Twitter. Twitter may be used to assess public sentiment toward current events, legislation, social movements and public figures, as well as the attitudes, feelings and opinions of various individuals. Opinion mining can be accomplished without manually reading tweets using Machine Learning and Deep Learning models. This data can be used to launch new policies, products, and events by governments and corporations alike. When it comes to categorising tweets according to their emotional content, there are a number of models that have been developed for classifying tweets as love, joy, sad, anger, fear, anxiety. The proposed Ensemble Classifier (LSTM-GRU) was determined to be the most effective after a thorough evaluation of its performance.