Bruno Ribeiro, Postdoctoral Fellow, Carnegie Mellon University (CMU)
19 de março de 2014
Resumo - Slides
Driven by outstanding success stories of Internet startups such as Facebook and The Huffington Post, recent studies have thoroughly described their growth. These highly visible online success stories, however, overshadow an untold number of similar ventures that fail. The study of website popularity is ultimately incomplete without general mechanisms that can describe both successes and failures. In this talk I present a model that is able to describe website popularity and predict evolution over time. My model is inspired by the writings of Nobel Laureate Herbert A. Simon. In a 1969 lecture Simon observed that many information systems were designed as if information was scarce, when the problem is just the opposite. "A wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it." My model equations consider Internet users' attention as a scarce resource that must be "consumed" by a website. Users' interactions with the website also create content that consumes the attention of other users. For instance, if the attention we dedicate to Facebook incites us to create content that helps Facebook capture a larger share of attention of our friends, then our friends will also produce more content (on average), which in turn captures a larger share of our attention. This positive attention feedback loop drives Facebook user activity up. But as the attention we are willing to dedicate to Facebook is limited, our (average) activity eventually stabilizes and remains stable. Conversely, if the share of our attention consumed by the website is not able to drive enough attention and content creation from our friends to keep our current attention level, then the negative attention feedback drives the website to its death.
Biografia resumida
Dr. Bruno Ribeiro is a Postdoctoral Fellow at the Carnegie Mellon University School of Computer Science. He received his B.Sc and M.Sc from the Federal University of Rio de Janeiro and Ph.D. in 2010 at the University of Massachusetts Amherst advised by Don Towsley. In 2012-2013 he was a visiting scholar at the Department Physics at Northeastern University. His interested are in data science, data mining, complex systems, and statistical models.
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