Emoji Anticipation and Prediction Using Deep Neural Network Model

Emojis are tiny pictorial depictions of feelings or objects that are frequently used in text messaging to enhance intercultural dialogue. Emojis are increasingly being used by users of social media sites like Twitter and Instagram in their text messages to express broader emotions that are frequently challenging to express in words alone. Combining text and emojis to express emotion has become a crucial part of how people communicate in the twenty-first century. In order to ascertain the connection between these text messages and the emojis used in them, a problem statement has been developed. In this study, we offer a technique for anticipating several emojis for a given text-based tweet message. Three modules make up the suggested model. The given text data is preprocessed in the first module, the model on which the data is trained is in the second, and a multi-class classifier is used in the third module to predict the emojis that the given text would evoke. This proposed deep neural network model aims to understand the underlying semantics of a text sentence using natural language processing techniques in order to predict appropriate emojis. Experiments performed utilizing a sizable data collection of Twitter-sourced real-world emoji usage.