The era of big data and analytics is opening up new possibilities for disaster management
(DM). Due to its ability to visualize, analyze and predict disasters, big data is changing the …

Social media analytics has become prominent in natural disaster management. In spite of a
large variety of metadata fields in social media data, four dimensions (ie space, time, content …

This study demonstrates a way of bringing an innovative data source, social media
information, to the government accounting information systems to support accountability to …

Social media websites can be used as a data source for mining public opinion on a variety
of subjects including climate change. Twitter, in particular, allows for the evaluation of public …

Although there is an unprecedented effort to provide adequate responses in terms of laws
and policies to hate content on social media platforms, dealing with hatred online is still a …

In this paper, we describe how we created two state-of-the-art SVM classifiers, one to detect
the sentiment of messages such as tweets and SMS (message-level task) and one to detect …

Sentiment analysis refers to the class of computational and natural language processing
based techniques used to identify, extract or characterize subjective information, such as …

Coastal communities faced with multiple hazards have shown uneven responses and
behaviors. These responses and behaviors could be better understood by analyzing real …

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 …

Sentiment analysis has been widely researched in the domain of online review sites with the
aim of generating summarized opinions of users about different aspects of products …