Predicting positive and negative links in online social networks
Proceedings of the 19th international conference on World wide web
Building a signed network from interactions in Wikipedia
Databases and Social Networks
Proceedings of the 2011 workshop on Knowledge discovery, modeling and simulation
Web Analytics for Security Informatics
EISIC '11 Proceedings of the 2011 European Intelligence and Security Informatics Conference
Predictive analytics in information systems research
MIS Quarterly
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Non-Equilibrium Social Science (NESS) emphasizes dynamical phenomena, for instance the way political movements emerge or competing organizations interact. This paper argues that predictive analysis is an essential element of NESS, occupying a central role in its scientific inquiry and representing a key activity of practitioners in domains such as economics, public policy, and national security. We begin by clarifying the distinction between models which are useful for prediction and the much more common explanatory models studied in the social sciences. We then investigate a challenging real-world predictive analysis case study, and find evidence that the poor performance of standard prediction methods does not indicate an absence of human predictability but instead reflects (1.) incorrect assumptions concerning the predictive utility of explanatory models, (2.) misunderstanding regarding which features of social dynamics actually possess predictive power, and (3.) practical difficulties exploiting predictive representations.