A Deep Learning Model for Opinion mining in Twitter Combining Text and Emojis

Abstract

Several approaches have been proposed to study opinions on Social Network Sites (SNS). Unfortunately, those works are not topic-sensitive and do not investigate the impact of emojis on text-based classification. In this paper, we propose a novel approach to predict the users’ opinions expressed through textual tweets and emojis. Thus, we construct an emoji sentiment lexicon. Then, we extract opinions from the text before considering both the text and emojis to see how they enhance the expression of opinions in SNS discussions. We conduct a set of benchmarks using several well-known machine learning algorithms, leading to an accuracy of 83, 7%.