and other Prosper personnel have provided us data support and tirelessly answered our questions about Prosper.com. Adam Weyeneth and other Prosper lenders have generously shared their prosper experience. We are grateful to the UMD Department of Economics, the Kauffman Foundation, and the Net Institute (www.netinst.org) for their generous financial support. An earlier draft has been circulated under the title "Dynamic Learning and Selection." This paper is independent of Prosper.com, all errors are our own, all rights reserved. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
This paper proposes a holistic view of a network organization's computing environment to examine computer virus propagation patterns. We empirically examine a large-scale organizational network consisting of both social network and technological network. By applying information retrieval techniques, we map nodes in the social network to nodes in the technological network to construct the composite network of the organization. We apply social network analysis to study the topologies of social and technological networks in this organization. We statistically test the impact of the interplay between social and technological network on computer virus propagation using a susceptible-infective-recovered epidemic process. We find that computer viruses propagate faster but reach lower level of infection through technological network than through social network, and viruses propagate the fastest and reach the highest level of infection through the composite network. Overlooking the interplay of social network and technological network underestimates the virus propagation speed and the scale of infection.Key words: social network analysis, interplay between social and technological networks, computer viruses 1 We gratefully acknowledge financial support from the NET Institute (www.netinst.org) and the Kauffman Foundation.3
We thank Danny Kim at NPD for answering our questions about the toy sales data and Kevin Mak at the Rotman Finance Lab for his assistance with assembling the stock price data. Molly Reckson provided capable research assistance. Financial support from the AIC Institute for Corporate Citizenship at the Rotman School of Management is gratefully acknowledged. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.