SENTIMENT ANALYSIS ON TWITTER

Computer Engineering

To propose a joint classification for tweets using big data and social networking site twitter. These days’ classification techniques using tweets is generally done by splitting a tweet in to words and not the whole tweet is taken in to consideration. So we thought of introducing a unique approach where tweets will be classified as whole and not in words. To enhance and expedite the concept, we thought of using distributed processing technology such as APACHE SPARK to help in classification as the tweets that are retrieved are in large numbers and not easy for a single machine to handle them so distributed system is preferable. The analyzed information results that are returned will be assembled and interpreted together on a single machine and the prediction returned are in the form of sentiment analysis as each tweet as a whole will have score and various sentiments will be attached with them such as positive and negative.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.