Emoticons and Their Effects on Sentiment Analysis of Twitter Data

Abstract

Several social media sites have come to become a growing source of data and information. The recent years have witnessed a massive and unprecedented growth of the World Wide Web. Usage of other social networking sites, Web Forums, and Blogs has also seen an ever-increasing trend. Twitter and Facebook, in particular, have become well-known means of communication over the Internet where millions of users share their opinions, reviews, experiences, thoughts, feelings, and preferences on different aspects of products or services, on a daily basis. This large volume of user-generated content contains sentiment-based sentences, which are expressions that describe the mood of the writer or his/her opinion towards a particular person/entity. This has resulted in the use of tweets, SMS messages, and other short informal texts being used in Sentiment Analysis (SA). In addition to text, emoticons are increasingly being used by people (specially youngsters) to express their feelings/sentiments that otherwise cannot be adequately communicated in words. Majority of the present SA systems do not consider emoticons as a part of analysis. However, emoticons are strong indicators of sentiments and can be considered as cues for analyzing sentiments. The main objective of this work is to determine whether emoticons can be used as reliable cues in SA, based on a comparison between SA conducted on tweets with emoticons and without emoticons