publication . Preprint . Conference object . 2011

prediction, social diffusion, and reputational ramifications

John W. Byers; Michael Mitzenmacher; Georgios Zervas;
Open Access English
  • Published: 07 Sep 2011
Abstract
Daily deal sites have become the latest Internet sensation, providing discounted offers to customers for restaurants, ticketed events, services, and other items. We begin by undertaking a study of the economics of daily deals on the web, based on a dataset we compiled by monitoring Groupon and LivingSocial sales in 20 large cities over several months. We use this dataset to characterize deal purchases; glean insights about operational strategies of these firms; and evaluate customers' sensitivity to factors such as price, deal scheduling, and limited inventory. We then marry our daily deals dataset with additional datasets we compiled from Facebook and Yelp user...
Subjects
free text keywords: Computer Science - Social and Information Networks, Physics - Physics and Society, The Internet, business.industry, business, Social diffusion, Information retrieval, World Wide Web, Social network, Scheduling (computing), Data science, Computer science, Reputation, media_common.quotation_subject, media_common
Funded by
NSF| NeTS FIND: A Network-Wide Hashing Infrastructure for Monitoring and Measurement
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 0721491
  • Funding stream: Directorate for Computer & Information Science & Engineering | Division of Computer and Network Systems
,
NSF| AF : Small : The Theory and Practice of Hash-Based Algorithms and Data Structures
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 0915922
  • Funding stream: Directorate for Computer & Information Science & Engineering | Division of Computing and Communication Foundations
,
NSF| FIA: Collaborative Research: A Content and Service Friendly Architecture with Intrinsic Security and Explicit Trust
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1040800
  • Funding stream: Directorate for Computer & Information Science & Engineering | Division of Computer and Network Systems

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Beer/Wine/Spirits 0.23 0.76 Body 0.10 0.76 Dental 0.01 0.77 Education -0.17 0.35 Entertainment -0.19 0.22 Escapes -0.60 0.24 * General 0.20 0.76 Getaway -0.68 0.26 ** Health -0.01 0.22 Home 0.31 0.76 Photography 0.20 0.76 Quick Bites -0.48 0.76 Restaurant 0.08 0.22 Retail -0.21 0.23 Services 0.19 0.22 Skincare -0.29 0.76 Specialty Food -0.25 0.23 Tour/Experience 0.52 0.76 Atlanta Reference level Boston -0.05 0.09 Chicago 0.16 0.08 * Dallas 0.09 0.10 Detroit -0.52 0.10 *** Houston 0.17 0.09 . Las Vegas -0.13 0.10 Los Angeles 0.17 0.09 . Miami -0.15 0.09 New Orleans 0.10 0.11 New York City 0.44 0.08 *** Orlando -0.30 0.09 ** Philadelphia 0.02 0.08 San Diego 0.14 0.08 . San Francisco 0.57 0.10 *** San Jose 0.16 0.11 Seattle 0.44 0.10 *** Tallahassee -0.55 0.11 *** Vancouver 0.45 0.10 *** Washington, D.C. 0.52 0.10 *** F -statistic 110 p-value < 2e-16 R-squared 0.67 Signi cance codes 0% *** 0.1% ** 1% * 5%

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publication . Preprint . Conference object . 2011

prediction, social diffusion, and reputational ramifications

John W. Byers; Michael Mitzenmacher; Georgios Zervas;