Social media offers participatory and collaborative structure and collective knowledge
building capacity to the public information and warning approaches. Therefore, the author …

Social media platforms provide active communication channels during mass convergence
and emergency events such as disasters caused by natural hazards. As a result, first …

Abstract Discriminative Correlation Filters (DCF) are efficient in visual tracking but suffer from
unwanted boundary effects. Spatially Regularized DCF (SRDCF) has been suggested to …

Feature engineering plays a vital role in big data analytics. Machine learning and data
mining algorithms cannot work without data. Little can be achieved if there are few features …

Social media platforms such as Twitter provide convenient ways to share and consume
important information during disasters and emergencies. Information from bystanders and …

Social media is an invaluable source of time-critical information during a crisis. However,
emergency response and humanitarian relief organizations that would like to use this …

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 …

Traditional machine learning, mainly supervised learning, follows the assumptions of closed-
world learning, ie, for each testing class, a training class is available. However, such …

Social media data have emerged as a new source for detecting and monitoring disaster
events. A number of recent studies have suggested that social media data streams can be …

The research field of crisis informatics examines, amongst others, the potentials and barriers
of social media use during disasters and emergencies. Social media allow emergency …