Sentimental Analysis of Tweets Using Machine Learning

The social media platforms Instagram, Facebook, Twitter, WhatsApp, and Telegram are some of the most effective for international communication. Individuals frequently share their ideas and feelings on Twitter and other social networks at various times. In order to determine if user-generated language reflects a positive, negative, or neutral view about an entity, this effort aims to develop a model that can analyses user- generated text utilizing voice conversation and emojis. A dataset of tweets from Twitter was generated using a Python Twitter scraper. To analyses people's emotions, machine learning techniques and approaches are applied and Text Blob to add a positive, negative, or neutral emoji to each tweet. The proposed system performs sentiment analysis using naive Bayes machine learning techniques.