Twitter Sentiment Analysis

This project is based on the prediction of the sentiments of tweets posted on Twitter by different account users.

Description

• Sentiment Analysis is a technique widely used in text mining. Twitter Sentiment Analysis, therefore means, using advanced text mining techniques to analyze the sentiment of the text in the form of positive, negative and neutral. It is also known as Opinion Mining. It is primarily used for analyzing conversations, opinions, and sharing of views for deciding business strategy, political analysis, and also for assessing public actions.

• With the Advancement of Natural Language Processing, this project is capable of Analysing the tweets posted on Twitter to predict the sentiment of the tweet i.e. positive, negative or neutral

• We are using Support Vector Classifier to predict the accurate results.

Technology Used

• Natural Language Processing
• Text Mining
• NLTK
• WordNetLemmatizer
• POS Tagging
• Stopwords
• Support Vector Machine Algorithm
• GridSearchCV
• pandas