Collective attention and the dynamics of group deals

Authors:
Mao Ye;Thomas Sandholm;Chunyan Wang;Christina Aperjis;Bernardo A. Huberman
Affiliations:
HP Labs, Palo Alto, CA, USA;HP Labs, Palo Alto, CA, USA;Stanford University, Stanford, CA, USA;HP Labs, Palo Alto, CA, USA;HP Labs, Palo Alto, CA, USA
Venue:
Proceedings of the 21st international conference companion on World Wide Web
Year:
2012

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Abstract

We present a study of the group purchasing behavior of daily deals in Groupon and LivingSocial and formulate a predictive dynamic model of collective attention for group buying behavior. Using large data sets from both Groupon and LivingSocial we show how the model is able to predict the success of group deals as a function of time.We find that Groupon deals are easier to predict accurately earlier in the deal lifecycle than LivingSocial deals due to the total number of deal purchases saturating quicker. One possible explanation for this is that the incentive to socially propagate a deal is based on an individual threshold in LivingSocial, whereas in Groupon it is based on a collective threshold which is reached very early. Furthermore, the personal benefit of propagating a deal is greater in LivingSocial.