Improving Emotion Recognition in Conversation using Text and Emoji Modalities

Due to the variability of human’s conversation, accurately identifying and distinguishing individual emotions from social media text is challenging. To overcome this limitation, this paper investigates to exploit emojis as a new source of information for emotion recognition in conversation. Emojis are received much interest for use as a salient feature in social media NLP systems. However, there is less explored in the domain of conversations in social media. This paper examines state-of-the-art emotion recognition algorithms in deep learning and evaluates impact of supplementing emojis as an additional feature for improving the algorithms. Emojis are transformed into corresponding vectors and combined with text embeddings. We propose two techniques of the combination at conversation and sentence levels. Our experiments show that emojis are effective for improving the accuracy of emotion recognition. We also perform a deeper analysis to find the most optimal dimension of emoji embedding in our recognition task.