DisasterNeedFinder: Understanding the Information Needs in the 2024 Noto Earthquake (Comprehensive Explanation)
Kota Tsubouchi, Shuji Yamaguchi, Keijirou Saitou, Akihisa Soemori, Masato Morita, Shigeki Asou
TL;DR
DisasterNeedFinder addresses the challenge of extracting on-the-ground information needs during large-scale disasters by fusing victim location data with search-query signals and defining intensity as query abnormalities to suppress media-driven noise. The framework employs privacy-preserving data preparation with obfuscation to inside/outside area labels and $k$-anonymization (set to $k=9$), followed by a linear-regression learning stage that uses spatial stopwords to reveal local needs. Validation during the 2024 Noto Peninsula earthquake shows DNF effectively tracks category-specific needs across Traffic, Water, Energy, Logistics, and Life Reconstruction, and aligns with media reports and PV data, demonstrating practical utility for rapid, area-specific disaster response. The work argues for broad generalization to other disasters and geographies, offering a data-driven, location-aware approach to inform timely relief and information services.
Abstract
We propose and demonstrate the DisasterNeedFinder framework in order to provide appropriate information support for the Noto Peninsula Earthquake. In the event of a large-scale disaster, it is essential to accurately capture the ever-changing information needs. However, it is difficult to obtain appropriate information from the chaotic situation on the ground. Therefore, as a data-driven approach, we aim to pick up precise information needs at the site by integrally analyzing the location information of disaster victims and search information. It is difficult to make a clear estimation of information needs by just analyzing search history information in disaster areas, due to the large amount of noise and the small number of users. Therefore, the idea of assuming that the magnitude of information needs is not the volume of searches, but the degree of abnormalities in searches, enables an appropriate understanding of the information needs of the disaster victims. DNF has been continuously clarifying the information needs of disaster areas since the disaster strike, and has been recognized as a new approach to support disaster areas by being featured in the major Japanese media on several occasions.