Detection and Scoring of Internet Slangs for Sentiment Analysis Using SentiWordNet

Abstract

The online information explosion has created great challenges and opportunities for both information producers and consumers. Understanding customer's feelings, perceptions and satisfaction is a key performance indicator for running successful business. Sentiment analysis is the digital recognition of public opinions, feelings, emotions and attitudes. People express their views about products, events or services using social networking services. These reviewers excessively use Slangs and acronyms to express their views. Therefore, Slang's analysis is essential for sentiment recognition. This paper presents a framework for detection and scoring of Internet Slangs (DSIS) using SentiWordNet in conjunction with other lexical resources. The comparative results show that proposed system outperforms the existing systems. (Fazal Masud Kundi, Shakeel Ahmad, Aurangzeb Khan, Muhammad Zubair Asghar. Detection and Scoring of Internet Slangs for Sentiment Analysis Using SentiWordNet. Life Sci J 2014;11(9):66-72). (ISSN:1097-8135). http://www.lifesciencesite.com . 10