document: Information spreading in context Information spreading processes are central to human interactions . Despite recent studies in online domains , little is known about factors that could affect the dissemination of a single piece of information . In this paper , we address this challenge by combining two related but distinct datasets , collected from a large scale privacy-preserving distributed social sensor system . We find that the social and organizational context significantly impacts to whom and how fast people forward information . Yet the structures within spreading processes can be well captured by a simple stochastic branching model , indicating surprising independence of context . Our results build the foundation of future predictive models of information flow and provide significant insights towards design of communication platforms .
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