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Automatic Prediction and Insertion of Multiple Emojis in Social Media Text

With the development of social media, many users are attracted by social platforms such as Twitter, Youtube, and TikTok. Emojis can be seen as a visual language inserted in texts to express emotions, attitudes, and situations. It is also widely used in social media communication, e.g., chit-chat and status sharing. The emojis can express more detailed and lively information beyond text information and can help chatbot become more like human beings. Current studies have explored how to predict single emoji according to a set of texts and context information. Some studies stated that people often add multiple emojis in texts and the different inserted positions corresponding to emojis' different functions. However, there is no study on inserting multiple emojis in texts. The latest advances in natural language processing and neural approaches have made it possible for chatbots to automatically add multiple emojis in chatbot's dialogue. In this article, we first construct a benchmark dataset contains more than 3.9 million comments in the video-sharing website Bilibili, and then analyze the features of emoji's usage and the relationships between emojis. Finally, a neural-based model is proposed to predict and insert multiple emojis in social media texts. The experiments and evaluation show our model got significant performance on predict and insert multiple emojis according to given sentences.