SentEmojiBot: Empathising Conversations Generation with Emojis
Akhilesh Ravi, Amit Yadav, Jainish Chauhan, Jatin Dholakia, Naman Jain, and Mayank Singh

TL;DR
SentEmojiBot is a novel chatbot that enhances empathetic conversation generation by integrating emojis with text, leveraging a new dataset and outperforming traditional models in empathy and understandability.
Contribution
This work introduces SentEmojiBot, the first system to utilize emojis for empathetic dialogue generation, and demonstrates its effectiveness through dataset creation and model evaluation.
Findings
BERT-based model outperforms vanilla transformer in empathy metrics.
Adding emojis increases perceived empathy by 9.8%.
Generated dialogues are more understandable and empathetic.
Abstract
The increasing use of dialogue agents makes it extremely desirable for them to understand and acknowledge the implied emotions to respond like humans with empathy. Chatbots using traditional techniques analyze emotions based on the context and meaning of the text and lack the understanding of emotions expressed through face. Emojis representing facial expressions present a promising way to express emotions. However, none of the AI systems utilizes emojis for empathetic conversation generation. We propose, SentEmojiBot, based on the SentEmoji dataset, to generate empathetic conversations with a combination of emojis and text. Evaluation metrics show that the BERT-based model outperforms the vanilla transformer model. A user study indicates that the dialogues generated by our model were understandable and adding emojis improved empathetic traits in conversations by 9.8%
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Taxonomy
TopicsTopic Modeling · AI in Service Interactions · Sentiment Analysis and Opinion Mining
