Convolutional Neural Network for Chinese Sentiment Analysis Considering Chinese Slang Lexicon and Emoticons

Abstract

Nowadays, social media have become the essential part of our lives. Internet slang is an informal language used in everyday online communication which quickly becomes adopted or discarded by new generations. Similarly, pictograms (emoticons/emojis) have been widely used in social media as a mean for graphical expression of emotions. People can convey delicate nuances through textual information when supported with emoticons, and the effectiveness of computer-mediated communication is also improved. Therefore, it is important to fully understand the influence of Internet slang and emoticons on social media. In this paper, we propose a convolutional neural network model considering Internet slang and emoticons for sentiment analysis of Weibo which is the most popular Chinese social media platform. Our experimental results show that the proposed method can significantly improve the performance for predicting sentiment polarity.