Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …

Studies on the role of social media in disaster management have so far focused mainly on
early phases of the disaster response process. Published evidence regarding the scope and …

Sentiment analysis through machine learning using Twitter data has become a popular topic
in recent years. Here we address the problem of sentiment analysis during critical events …

The main purpose of this paper was to explore the effect of social media marketing activities
(SMMAs) on brand equity (BEQ) through a moderated mediation analysis of brand …

The study of big data analytics (BDA) methods for the data-driven industries is gaining
research attention and implementation in today's industrial activities, business intelligence …

This article provides a literature review of state-of-the-art machine learning (ML) algorithms
for disaster and pandemic management. Most nations are concerned about disasters and …

People start posting tweets containing texts, images, and videos as soon as a disaster hits
an area. The analysis of these disaster-related tweet texts, images, and videos can help …

Citizens with different demographic characters presented varying responses and behaviors
in the same disasters. Their divergent responses can impact their actual damages during …

Abstract North and South Kivu provinces in the Eastern part of the Democratic Republic of
the Congo (DRC) are still confronted by both natural and manmade disasters and are …

Rapid appraisal of damages related to hazard events is of importance to first responders,
government agencies, insurance industries, and other private and public organizations …