Speaker
Description
One of the main goals of TA4 is effective science communication and outreach for maximizing the impact of DAPHNE4NFDI. For managing the outreach activities with less time and sources we explore the integration of Large Language Models (LLMs) to automate key aspects of outreach in TA4 at DAPHNE4NFDI.
We propose an LLM-driven workflow for automatization of (1) event summarization, generating structured reports, social media posts, and news from workshops, meetings and conferences; and (2) social media monitoring and insights, employing AI-based analytics to optimize content strategies and track audience engagement.
Preliminary tests demonstrate that LLMs can generate targeted outreach messages, and provide data-driven insights into audience behavior. This approach serves as a model for integrating LLMs into research outreach, supporting more efficient science communication.
