In contexts ranging from public goods provision to information collection, a player's well-being depends on his or her own action as well as on the actions taken by his or her neighbours. We provide a framework to analyse such strategic interactions when neighbourhood structure, modelled in terms of an underlying network of connections, affects payoffs. In our framework, individuals are partially informed about the structure of the social network. The introduction of incomplete information allows us to provide general results characterizing how the network structure, an individual's position within the network, the nature of games (strategic substitutes vs. complements and positive vs. negative externalities) and the level of information shape individual behaviour and payoffs. Copyright © 2009 The Review of Economic Studies Limited.
Empirical work shows that a large majority of individuals get most of their information from a very small subset of the group, viz., the influencers; moreover, there exist only minor differences between the observable characteristics of the influencers and the others. We refer to these empirical findings as the Law of the Few. This paper develops a model where players personally acquire information and form connections with others to access their information. Every (robust) equilibrium of this model exhibits the law of the few. (JEL D83, D85, Z13)
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The growth of the Internet and assorted technologies has made it possible to collect and process detailed information on social networks. This article investigates how firms (and governments) can harness the power of social networks to promote their goals. We show that the optimal use of social networks leads to higher sales and greater profits. However, an increase in the level and dispersion of social interaction can increase or decrease the optimal influence strategy and profits of the player, depending on the content of the interaction. Optimal influence strategies will target individuals with low or high connections, depending on the content of interaction. Finally, the returns to investing in market research on social networks are greater in more unequal networks. Copyright (c) 2009, RAND..
We study games in which a network mediates strategic spillovers and externalities among the players. How does a planner optimally target interventions that change individuals' private returns to investment? We analyze this question by decomposing any intervention into orthogonal principal components, which are determined by the network and are ordered according to their associated eigenvalues. There is a close connection between the nature of spillovers and the representation of various principal components in the optimal intervention. In games of strategic complements (substitutes), interventions place more weight on the top (bottom) principal components, which reflect more global (local) network structure. For large budgets, optimal interventions are simple—they essentially involve only a single principal component.
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