Social media information sharing for natural disaster response

Abstract

Social media has become an essential channel for posting disaster-related information, which provides governments and relief agencies real-time data for better disaster management. However, research in this field has not received sufficient attention, and extracting useful information is still challenging. This paper aims to improve disaster relief efficiency via mining and analyzing social media data like public attitudes toward disaster response and public demands for targeted relief supplies during different types of disasters. We focus on different natural disasters based on properties such as types, durations, and damages, which contains a total of 41,993 tweets. In this paper, public perception is assessed qualitatively by manually classified tweets, which contain information like the demand for targeted relief supplies, satisfactions of disaster response, and public fear. Public attitudes to natural disasters are studied via a quantitative analysis using eight machine learning models. To better provide decision-makers with the appropriate model, the comparison of machine learning models based on computational time and prediction accuracy is conducted. The change of public opinion during different natural disasters and the evolution of peoples' behavior of using social media for disaster relief in the face of the identical type of natural disasters as Twitter continues to evolve are studied. The results in this paper demonstrate the feasibility and validation of the proposed research approach and provide relief agencies with insights into better disaster management.

The application of knowledge management in disaster management: past, present and future trends

“…Extraction of disaster information and improvement of situational awareness (Power et al , 2014; Karami et al , 2020). Disaster trajectory detection (Crooks et al , 2013; Earle et al , 2011) and evaluate the social response and network performance (Fang et al , 2019; Dong et al , 2021). The multifunctional characteristic of social media facilitates disaster management; thus, the application would be useful in various ways, including disaster preparedness and postrecovery.…”

Cities under fire: Crisis communication on home front versus frontline cities' Facebook pages during operation ‘guardian of the walls’

“…These platforms were proven to be highly efficient and effective for communicating prompt messages regarding emergencies and crises on a large scale to citizens and residents (Hagen et al, 2020; Y. Li et al, 2020; Roy et al, 2020). Furthermore, social media platforms can provide government agencies and decision‐makers with the most up‐to‐date citizen sentiment regarding a developing crisis and assist them in creating a proper response and acting accordingly (Dong et al, 2021; Tagliacozzo, 2018; Zhou et al, 2018). This practice is especially relevant in natural disasters such as floods (Rossi et al, 2018), hurricanes (Yang & Stewart, 2019) or earthquakes when there is a combined need for preparedness, rescue and relief efforts (L. Li et al, 2018; Pourebrahim et al, 2019; Scott & Errett, 2018; Taylor et al, 2023).…”

Machine Learning Models for Mining Social Media Data for Effective Natural Disaster Assessment

“…Furthermore, the potential of social media data to improve disaster relief effectiveness by gauging public perception and attitudes towards various natural disasters is examined in (Dong et al 2021). The swiftness of social media messages in disseminating updates, surpassing traditional sources, provides unique perspectives on events and community requirements.…”