Internet economics and monetization

The Web has become as a major economic phenomenon, serving both as a new platform for traditional transactions such as business-to-business and business-to-consumer commerce, as well as an arena for a variety of new economic activities ranging from online advertising, digital payment systems, bandwidth provisioning, peer-to-peer lending, and crowdsourcing.

The WWW track on Internet Economics and Monetization is a forum for theoretical and applied research related to the modeling, analysis, and design of web-specific economic activities and incentive systems, and computational advertising and ad selection for all available online advertising formats. The track will be interdisciplinary in nature, welcoming any research related to economic aspects of the Web.


Relevant topics include (but are not limited to) :

  • Internet auctions, markets, and exchanges
  • Computational advertising: Sponsored search, content match, graphical ads delivery, targeting
  • Machine learning and data mining in the context of Internet monetization
  • Economics aspects of online reviews, reputations, and ratings
  • Monetizing digital media, user generated content, and the social web
  • User-experience design aspects of Web monetization mechanisms
  • Web analytics for e-commerce
  • Economics of data and digital goods
  • Incentives in crowdsourcing and human computation
  • Advertising infrastructure: tools, platforms, networks, exchanges, automation, audience intelligence
  • Economic approaches to spam/fraud control
  • E-commerce issues in cloud computing and and Web apps
  • Mobile web advertising and location-based e-commerce
  • Decision-theoretic and game-theoretic modeling of online behavior
  • Empirical and theoretical analysis of online labor markets

Area Chairs

  • Arpita Ghosh (Cornell University)
  • Vanja Josifovski (Google)

TPC Members

  • Liad Blumrosen (Department of Economics, The Hebrew University)
  • Anirban Dasgupta (Yahoo! Research)
  • Nikhil Devanur (Microsoft Research)
  • Gagan Goel (Google Research)
  • Ashish Goel (Stanford University)
  • Sreenivas Gollapudi (Microsoft Research)
  • Patrick Hummel (Google Inc.)
  • Krishnamurthy Iyer (Cornell University)
  • Kamal Jain (eBay Research)
  • Ramesh Johari (Stanford University)
  • Radu Jurca (Google Inc. Switzerland)
  • Sebastien Lahaie (Microsoft Research)
  • Ron Lavi (The Technion — Israel Institute of Technology)
  • Jeffrey Mackie-Mason (University of Michigan)
  • Preston McAfee (Google)
  • Aranyak Mehta (Google)
  • Vahab Mirrokni (Google Research)
  • S Muthukrishnan (Rutgers University and Microsoft Research)
  • Uri Nadav (Google)
  • Michael Ostrovsky (Stanford University)
  • David Pennock (Microsoft Research)
  • Michael Schapira (Yale University & U.C. Berkeley)
  • Eric Sodomka (Brown University)