Incentive Mechanisms for Users and Platforms of Social Networks

The literature on social networks in economics, both empirical and theoretical has been growing substantially in the last few decades. Much of this growth can be attributed to the proliferation of online social networks. Theory papers have provided important models for the process of network formation and the spread of influence within networks (Jackson and Wolinsky, 1996; Mutuswami and Winter, 2002; Kempe et al., 2003; Ballester et al., 2006; Jackson, 2011). Empirical papers used existing data as well as field experiments to study how behavior diffuses within a network (Ichino and Maggi, 2000; Sacerdote, 2001; Mas and Moretti, 2009; Banerjee et al., 2013). There is also emerging literature on social media platforms (Ghosh and McAfee, 2011; Ashish, and Ronaghi, 2012; Ghosh and Hummel, 2014).

Most of the Graph/Game theory literature of social media treats the network structure as given and fixed and focuses on the flow of information through the network and on users' strategic considerations. The role of the platform itself is typically left un-modeled. Our objective in this project is to develop and analyze models of social media using primarily tools in Game Theory and Graph Theory. Our approach is different from much of the existing literature in that we treat the platform's owners/managers as a major player in the social media game - one that has an enormous influence on the activity that takes place in the network. This influence arises through a certain degree of control over the structure of the social network and almost full control over users' available actions. Our modeling efforts will not only focus on users' motives and preferences. The motives and preferences of the platform itself are equally important. These preferences critically depend on the platform's business model. They can be aligned with users' preferences in some business models and conflicting with users' preferences in others. We note here that platforms' preferences and interests are key elements in models that aspire to provide policy implications. If platforms and users have identical interests there is little need for intervention. It is when these interests are conflicting that intervention by governments or international organizations in certain circumstances might be required.

Our first objective will be to identify areas in which the interests of the platform and its users are conflicting and areas in which they coincide. We will also study mechanisms and rules for social media that can bring about Pareto improvements in SM content quality or substantial improvement to users' welfare with no major revenue losses to the platform. More specific questions we plan to address are:
What are the optimal network structures from the point of view of the platform and what sort of implications such structure might have on the distribution of users' right to express themselves and their overall welfare? How do social media platforms based on undirected graphs (e.g. Facebook and LinkedIn) differ from those based on directed graphs (Twitter and Instagram) in terms of users' welfare? What is the optimal policy for the flow of content in the network (e.g., feed news policy) from the point of view of both the platform and users? What are the incentives behind users' spreading abusive content and fake news through the network, and how can such ill incentives be mitigated?

Our project is designed to have a substantial policy impact through collaboration with organizations such as Ofcom, FCC. Promisingly enough the initiative for such collaboration came from Ofcom following the appearance of our discussion paper on the topic. We were invited to present our work at Ofcom and we are now collaborating with Ofcom in organizing a conference on this subject where key policy people from Ofcom, the FCC, Facebook and Google have confirmed their participation. We plan to hold regular meetings with people at Ofcom during the implementation of the project.