Sensemaking of Socially-Mediated Crisis Information

Document Type

Conference Proceeding

Publication Date

1-1-2024

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.

Identifier

105000174402 (Scopus)

ISBN

[9798891761117]

Publication Title

HCI+NLP 2024 - 3rd Workshop on Bridging Human-Computer Interaction and Natural Language Processing, Proceedings of the Workshop

First Page

74

Last Page

81

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