Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Graph evolution: Densification and shrinking diameters
ACM Transactions on Knowledge Discovery from Data (TKDD)
Comments on "A New Product Growth for Model Consumer Durables"
Management Science
Microscopic evolution of social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Hot today, gone tomorrow: on the migration of MySpace users
Proceedings of the 2nd ACM workshop on Online social networks
Predicting the popularity of online content
Communications of the ACM
The life and death of online groups: predicting group growth and longevity
Proceedings of the fifth ACM international conference on Web search and data mining
Multi-scale dynamics in a massive online social network
Proceedings of the 2012 ACM conference on Internet measurement conference
Social resilience in online communities: the autopsy of friendster
Proceedings of the first ACM conference on Online social networks
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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 work we present six years of the daily number of users (DAU) of twenty-two membership-based websites - encompassing online social networks, grassroots movements, online forums, and membership-only Internet stores - well balanced between successes and failures. We then propose a combination of reaction-diffusion-decay processes whose resulting equations seem not only to describe well the observed DAU time series but also provide means to roughly predict their evolution. This model allows an approximate automatic DAU-based classification of websites into self-sustainable v.s. unsustainable and whether the startup growth is mostly driven by marketing & media campaigns or word-of-mouth adoptions.