Abstract
Aspects of the disclosure are directed to real-time message sentiment augmentation by emojis. A large language model (LLM) can determine, for each message that is shared in a virtual chat, a presumed sentiment of an author of a message and a presumed audience reaction toward the latest message in the virtual chat. The LLM can identify an emoji that captures the presumed sentiment of the author. The LLM-identified emoji can be visually associated with an icon/avatar that corresponds to the author. The LLM can identify emojis that capture the presumed audience reaction toward the latest message in the virtual chat. The LLM-identified emojis can be visually associated with the latest message in the virtual chat.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Savage, Gregory and Yung, Alex, "Real-Time Message Sentiment Augmentation by Emoji Symbols", Technical Disclosure Commons, (December 04, 2024)
https://www.tdcommons.org/dpubs_series/7620