Ranked Rule Based Approach for Sentiment Analysis

Today, large population use social networking sites like Facebook, Twitter, LinkedIn etc. Through social media, people share messages, photos. They also impart information about a particular event or specific situation. There is limited research on crowd management to handle a disaster. We should focus on Crowd Management using Sentiment Analysis as a tool for safety in some events or situations. People convey their emotion about crowd using social sites. Crowd-related issues encountered day to day life such as stations, shopping malls, and stadiums or some events like marriage which may cause congestion and due to that some people may be injured or causes death. Peoples post their sentiments through Twitter, LinkedIn etc.In this paper, we consider traffic jam event where traffic will be able to move or will not be able to move. For this purpose, tweets are collected from social networking site Twitter. Human expressions are expressed through Natural Language Processing and then calculate polarity of sentiment using rule-based approach. User’s opinion is classified into positive, negative or neutral Sentiment. Polarity score of sentence is calculated through SND pattern. Users may enter false tweets which will decrease accuracy of system. To increase accuracy of system along with polarity score, we also consider polling based on user ranking in our proposed system.