Sentiment Analysis is a process of extracting feature from user’s thoughts, views, feelings and opinions which they post on any social network websites. The result of sentiment analysis is classification of natural language text into classes such as positive, negative and neutral. The amount of data generated from social network sites is huge; this data is unstructured and cannot give any meaningful information until it is analyzed. Thus, to make this huge amount of data useful we perform sentiment analysis, i.e. extracting feature from this data and classify them. Sentiment analysis is very necessary in today’s world, as people always get affected by the thinking and opinions other people.
Objectives of this project are: The main objective of this thesis work is to perform the sentiment analysis on Indian Political Parties like BJP, INC and AAP, such that people opinions about these parties progress, workers, policies, etc. which are extracted from Twitter. Thus to achieve this objective we build a classifier based on supervised learning and perform live sentiment analysis on data collected of different political parties. Tools used: 1.Flask 2.Azure services: 3.Twitter API 4.Tweepy a python module 5.Textblob 6.nltk 7.Twitter API Implementation: As our goal is to achieve sentiment analysis for data provided from Twitter. We are going to build a classifier which consists of different machine learning classifiers. Once our classifier is ready and trained we are going to follow the steps Step-1 First we are going to stream tweets in our build classifier with the help of Tweepy library in python Step-2 Then we pre-process these tweets, so that they can be fit for mining and feature extraction. Step-3 After pre-processing we pass this data in our trained classifier, which then classify them into positive or negative class based on trained results. Conclusion : Sentiment analysis is used to identifying people’s opinion, attitude and emotional states. The views of the people can be positive or negative. Commonly, parts of speech are used as feature to extract the sentiment of the text. An adjective plays a crucial role in identifying sentiment from parts of speech. Sometimes words having adjective and adverb are used together then it is difficult to identify sentiment and opinion.