Data Preprocessing for Efficient Sentimental Analysis
Shreyas Wankhede, Ranjit Patil, Sagar Sonawane, Ashwini M. Save · 2018
Sentiment analysis is an important research area that identifies the people's sentiments, opinions and emotions underlying a text. As the use of social media is increasing day by day, it plays an essential role in communication through technology. Twitter, which is one of the popular and largely used social media platforms for communication has more than 200 million tweets per day. Tweets are short in length and due to limited size of tweets people generally commit some mistakes while tweeting so pre-processing is necessary. The use of modern emoticons which are known as emojis that is largely used in social media communications that conveys variety of emotions. The purpose of this paper is to use N -gram method and Hidden Markov Model for Spell-Checking and Correction of tweets and also Emoji Sentiment Ranking method which is used to evaluate sentiment mapping of emojis by using sentiment polarity such as negative, neutral, or positive.