Digital forms of citizen communication with response organizations through social media are
becoming more widespread during disasters. Public agencies often use this information to …

The objective of this study is to propose and test a hybrid machine learning pipeline to
uncover the unfolding of disaster events corresponding to different locations from social …

Due to the increasing incidence of natural hazards and population growth in hazard-prone
areas, research and practices on improving disaster resilience have gained significant …

Situational awareness tries to grasp the important events and circumstances in the physical
world through sensing, communication, and reasoning. Tracking the evolution of changing …

Real-time information sharing and propagation using social media such as Twitter has
proven itself as a potential resource to improve situational awareness in a timely manner for …

The objective of this study is to propose and test a methodological framework that integrates
natural language processing and meta-network analysis to leverage social media data for …

Social media such as Twitter offers a tremendous amount of data throughout an event or a
disastrous situation. Leveraging social media data during a disaster is beneficial for effective …

Disaster response plays a vital role in reducing disaster impacts and building resilient
communities. Efficient disaster response relies heavily on timely information describing …

Traditional data collection methods such as remote sensing and field surveying often fail to
offer timely information during or immediately following disaster events. Social sensing …

During a natural disaster, mining messages from social media platforms can facilitate local
agencies, rescue teams, humanitarian aid organizations, etc., to track the situational …