  Emojis, which encapsulate semantics beyond mere words or phrases, have become
prevalent in social network communications. This has spurred increasing
scholarly interest in exploring their attributes and functionalities. However,
emoji-related research and application face two primary challenges. First,
researchers typically rely on crowd-sourcing to annotate emojis in order to
understand their sentiments, usage intentions, and semantic meanings. Second,
subjective interpretations by users can often lead to misunderstandings of
emojis and cause the communication barrier. Large Language Models (LLMs) have
achieved significant success in various annotation tasks, with ChatGPT
demonstrating expertise across multiple domains. In our study, we assess
ChatGPT's effectiveness in handling previously annotated and downstream tasks.
Our objective is to validate the hypothesis that ChatGPT can serve as a viable
alternative to human annotators in emoji research and that its ability to
explain emoji meanings can enhance clarity and transparency in online
communications. Our findings indicate that ChatGPT has extensive knowledge of
emojis. It is adept at elucidating the meaning of emojis across various
application scenarios and demonstrates the potential to replace human
annotators in a range of tasks.
