Share Analytics examines query processing and analytics issues arising in the context of the sharing economy. It is developed as a research project at the Department of Computer Science, University of Toronto.
Motivation: The sharing economy (manifested by services such as AirBnB, Uber among others, but by traditional online markeplaces as well) allows individuals to provide services (such as apartment rental, expertise etc) directly to consumers. Aside from the fundamental economic innovations of this model, it poses interesting challenges from a data analysis perspective. Consider the example of AirBnB in which hosts offer services (rooms for rent) directly to renters. How can hosts optimize their presence in such a service (optimize their revenue, offer the best amenities that would result to maximum monetary gain, which days should prices be higher etc). In this project we are using the example of AirBnB to study several research questions arising in this context. Our current prototype is available from this link
Novel Query Models We are also developing new ways to query and analyze data in this context motivated by the unique optimization objectives of these platforms. For example in a platform such as AirBnB how to identify the ammenities a host has to offer in order to maximize their revenue?
An experimental Analysis of Pricing and Associated Parameters in AirBnB, A. Sherman and Nick Koudas