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Proc. of the IFIP WG 6.5 working conference on Computer-based message services
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Flu detector: tracking epidemics on twitter
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Generating predictive movie recommendations from trust in social networks
iTrust'06 Proceedings of the 4th international conference on Trust Management
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Our daily life leaves an increasing amount of digital traces, footprints that are improving our lives. Data-mining tools, like recommender systems, convert these traces to information for aiding decisions in an ever-increasing number of areas in our lives. The feedback loop from what we do, to the information this produces, to decisions what to do next, will likely be an increasingly important factor in human behavior on all levels from individuals to societies. In this essay, we review some effects of this feedback and discuss how to understand and exploit them beyond mapping them on more well-understood phenomena. We take examples from models of spreading phenomena in social media to argue that analogies can be deceptive, instead we need to fresh approaches to the new types of data, something we exemplify with promising applications in medicine.