Summary of Emojis Decoded: Leveraging Chatgpt For Enhanced Understanding in Social Media Communications, by Yuhang Zhou et al.
Emojis Decoded: Leveraging ChatGPT for Enhanced Understanding in Social Media Communications
by Yuhang Zhou, Paiheng Xu, Xiyao Wang, Xuan Lu, Ge Gao, Wei Ai
First submitted to arxiv on: 22 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper explores the use of Large Language Models (LLMs) like ChatGPT in emoji-related research, aiming to validate their effectiveness as an alternative to human annotators. The study assesses ChatGPT’s capabilities in handling previously annotated and downstream tasks, with a focus on its ability to explain emoji meanings and enhance clarity in online communications. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Emoji are used extensively in social media, but understanding their meaning can be challenging due to subjective interpretations by users. To overcome this limitation, the paper uses ChatGPT to annotate emojis, demonstrating its potential to replace human annotators. The study shows that ChatGPT has extensive knowledge of emojis and is adept at explaining their meanings across various scenarios. |
