Abstract
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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References
Henry, A.D., Dietz, T.: Information, networks, and the complexity of trust in commons governance. International Journal of the Commons 5(2) (2011)
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© 2013 Springer-Verlag Berlin Heidelberg
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Stickgold, E., Lofdahl, C., Farry, M. (2013). Trust Metrics and Results for Social Media Analysis. In: Greenberg, A.M., Kennedy, W.G., Bos, N.D. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2013. Lecture Notes in Computer Science, vol 7812. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37210-0_50
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DOI: https://doi.org/10.1007/978-3-642-37210-0_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37209-4
Online ISBN: 978-3-642-37210-0
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