Abstract
In times of crisis, the human mind is often a voracious information forager. It might not be immediately apparent what one wants or needs, and people frequently look for answers to their most pressing questions and worst fears. In that context, the pandemic has demonstrated that social media sources, like erstwhile Twitter, are a rich medium for data-driven communication between experts and the public.However, as lay users, we must find needles in a haystack to distinguish credible and actionable information signals from the noise. In this work, we leverage the literature on crisis communication to propose an AI-driven sensemaking model that bridges the gap between what people seek and what they need during a crisis. Our model learns to contrast social media messages concerning expert guidance with subjective opinion and enables semantic interpretation of message characteristics based on the communicative intent of the message author. We provide examples from our tweet collection and present a hypothetical social media usage scenario to demonstrate the efficacy of our proposed model.- Anthology ID:
- 2024.hcinlp-1.7
- Volume:
- Proceedings of the Third Workshop on Bridging Human--Computer Interaction and Natural Language Processing
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Su Lin Blodgett, Amanda Cercas Curry, Sunipa Dey, Michael Madaio, Ani Nenkova, Diyi Yang, Ziang Xiao
- Venues:
- HCINLP | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 74–81
- Language:
- URL:
- https://aclanthology.org/2024.hcinlp-1.7
- DOI:
- Cite (ACL):
- Vrushali Koli, Jun Yuan, and Aritra Dasgupta. 2024. Sensemaking of Socially-Mediated Crisis Information. In Proceedings of the Third Workshop on Bridging Human--Computer Interaction and Natural Language Processing, pages 74–81, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- Sensemaking of Socially-Mediated Crisis Information (Koli et al., HCINLP-WS 2024)
- PDF:
- https://preview.aclanthology.org/ingestion-checklist/2024.hcinlp-1.7.pdf