This tutorial introduces the mechanism design for information sharing in a social network such that truthful information will be fully propagated/diffused in the network. These diffusion mechanisms challenge the costly advertising mechanisms used by search engines and social media by eliminating the costly platforms and ensuring revenue-increase for the advertisers.
The literature of mechanism design has traditionally assumed that the set of participants are fixed and are known to the mechanism (i.e. the market owner) in advance. However, in practice the market owner can only directly reach a small number of participants. In order to get more participants, the market owner often needs costly promotions via, e.g., Google, Facebook or Twitter, but the impact of the promotions is often unpredictable. That is, the revenue-increase that the market owner gets from the promotions may not cover the costs of the promotions.
To solve this dilemma, we build the promotion inside the market mechanism without using any advertising platform. The promotion guarantees that the market owner will never lose and does not need to pay if the promotion is not beneficial to her. This is achieved by incentivizing people who are aware of the market to further propagate the information to their neighbors. They will be rewarded only if their diffusion effort is beneficial to the market owner, so the promotion is cost-free to some extent. This tutorial will discuss how to design such cost-free promotions, analyze some essential examples and show the rich challenges we still face.
The target audience are PhD students and researchers who are interested in Algorithmic Game Theory, Mechanism Design/Auctions, Information Propagation in Social Networks.
The research direction is new and has not been well explored yet, and our novel solutions have attracted the community. We believe the challenge itself is very interesting to many AI researchers, especially those who work on game theory and social network related topics. It plays an essential role for the next generation of sale promotions, and it challenges the advertising models (like sponsored search auctions) that search engines are currently using.
Dr. Dengji Zhao is an Assistant Professor at ShanghaiTech University, China. He received double Ph.D. (2012) degrees in Computer Science from University of Western Sydney and University of Toulouse, and received double M.Sc. (2009) degrees in Computational Logic from Technische Universität Dresden and Universidad Politécnica de Madrid. Before joining ShanghaiTech, he was a postdoc (2013-2014) working with Prof. Makoto Yokoo (the first AAAI Fellow in Asia) and a research fellow (2014-2016) working with Prof. Nick Jennings (the first Regius Professor of Computer Science, UK).