Presented at the The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013), Washington, DC (April 2013)
Social media has changed the information landscape for a variety of events including natural disasters, demonstrations, and violent crises. During these events, people use a variety of social media, such as Twitter, to share information with the world. Given the massive amount of data generated, it is difficult to identify the valuable information in a sea of noise. In this study, we focus on a universal contributing factor to information value–trust–which is analyzed in two steps. Leveraging the theory of trust in information, a set of metrics is developed that focus on trusted relationships and behavioral indicators of trustworthiness within social media. Second, these trust metrics are tested on an anonymized data set and their results presented.
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