IRJET - Implementation of Twitter Sentimental Analysis According to Hash Tag

This document proposes a model for analyzing sentiment from tweets using hashtags. It involves collecting tweets, preprocessing the data by removing URLs and stopwords, training a classifier using Naive Bayes, and classifying tweets as positive, negative, or neutral. Hashtags are also classified to help organize tweets by topic. The proposed system is intended to help large companies understand public sentiment about their brands by analyzing tweets in real-time.