A BigData approach for sentiment analysis of twitter data using Naive Bayes and SVM Algorithm

Abstract

Data mining and sentiment analysis are two most versatile research areas in field of real time knowledge extraction. Real time twitter data analysis can plays very crucial role to observe the thinking and view point of people and users. Nowadays, social networking sites have become centric points to share your thoughts and viewpoints. Analysis of social networking data can help a lot to observe trend of society. It can also help to derive user interest and hidden activities. Sentiment analysis is the approach to determine whether piece of writing is positive, negative or neutral. It also help to derive user opinion and attitude of writer. Sentiment analysis of twitter user can help to track eventual view point of user. Country wise accumulative view point can help to derive overall opinion of country citizens and their thinking criteria. This work has proposed sentiment analysis model to observe positive and negative view point of different countries based on sentiment analysis approach. The complete work will be implemented using Hadoop Ecosystem to perform parallel processing on large data.