An emotional step toward automated trust detection in crisis social media

To this date, research on crisis informatics has focused on the detection of trust in Twitter data through the use of message structure, sentiment, propagation and author. Little research has examined the usefulness of these messages in the crisis response domain. In this paper, we characterize tweets, which are perceived useful or trustworthy, and determine their main features as one possible dimension to identify useful messages in case of crisis. In addition, we examine perceived emotions of these messages and how the different emotions affect the perceived usefulness and trustworthiness. Our analysis is carried out on two datasets gathered from Twitter concerning Hurricane Sandy in 2012 and the Boston Bombings in 2013. The results indicate that there is a high correlation between trustworthiness and usefulness, and, interestingly, that there is a significant difference in the perceived emotions that contribute to each of these. Our findings are poised to impact how messages from social media data are analyzed for use in crisis response.