Improving the Utility of Social Media Data to Emergency Responders through Emotional Content Detection
Shane E. Halse, Andrea Tapia · International Journal of Information Systems for Crisis Response and Management · 2016
In the following paper, we will present an alternate method for the detection of emotional content within social media data. Current research has presented the traditional bag-of-words method in which a predefined corpus is used to measure the emotional context of each word within a message. Here we present a method in which a small subset of the data is labeled to generate a corpus which is then used to detect emotional content within the data. This research is being conducted on the dataset from hurricane Sandy in 2012. Our findings show an improvement upon the bag-of-words method. These findings would further the current research in improving the utilization of social media data within crisis response. In doing this we allow the average citizen to provide beneficial data to those in decision making roles.