Twitter Sentiment Analysis Project

This project predicts the sentiments of tweets posted on Twitter by different users using the concepts of Natural Language Processing

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 evolution of new technologies such as 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

• As a part of Supervised Learning, we are using the Support Vector Machines algorithm to predict the results.

Technology Used

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