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Networks pervade social and economic life, and they play a prominent role in explaining a huge variety of social and economic phenomena. Standard economic theory did not give much credit to the role of networks until the early 1990s, but since then the study of the theory of networks has blossomed. At the heart of this research is the idea that the pattern of connections between individual rational agents shapes their actions and determines their rewards. The importance of connections has in turn motivated the study of the very processes by which networks are formed. In Connections, Sanjeev

Introduction -- Networks : concepts and empirics -- Games on networks -- Coordination and cooperation -- Social learning -- Social networks in labor markets -- Strategic network formation : concepts -- One-sided link formation -- Two-sided link formation -- Research collaboration among firms

Copyright © 2017 The Authors. Modern economies rely heavily on their infrastructure networks. These networks face threats ranging from natural disasters to human attacks. As networks are pervasive, the investments needed to protect them are very large; this motivates the study of targeted defense. What are the "key" nodes to defend to maximize functionality of the network? What are the incentives of individual nodes to protect themselves in a networked environment and how do these incentives correspond to collective welfare?. We first provide a characterization of optimal attack and defense in terms of two classical concepts in graph theory: separators and transversals. This characterization permits a systematic study of the intensity of conflict (the resources spent on attack and defense) and helps us identify a new class of networks—windmill graphs—that minimize conflict. We then study security choices by individual nodes. Our analysis identifies the externalities and shows that the welfare costs of decentralized defense in networks can be very large. ; Both authors thank the European Research Area Complexity Net for financial support. Marcin Dziubi ́nskiwas supported by the Strategic Resilience of Networks project realized within the Homing Plus program ofthe Foundation for Polish Science and was co-financed by the European Union from the Regional Devel-opment Fund within Operational Programme Innovative Economy (grants for innovation). Sanjeev Goyalacknowledges financial support from a Keynes Fellowship and the Cambridge INET Institute.

The interaction between community and markets remains a central theme in the social sciences. The empirical evidence is rich: in some instances, markets strengthen social ties, while in others they undermine them. The impact of markets on inequality and welfare also varies widely. This paper develops a model where individuals in a social network choose whether to participate in their network and whether to participate in the market. We show that individual behavior is defined by the q-core of the network and the key to understanding the conflicting evidence is whether the market and the network are complements or substitutes. (JEL D63, D85, J15, L82, O15, Z13, Z31)

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)

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.

The important role of friends, neighbors and colleagues in shaping individual choices has been brought out in a number of studies over the years. The presence of significant 'local' influence in shaping individual behavior suggests that firms, governments and developmental agencies should explicitly incorporate it in the design of their marketing and developmental strategies. This paper develops a framework for the study of optimal strategies in the presence of social interaction. We focus on the case of a single player who exerts costly effort to get a set of individuals – engaged in social interaction – to choose a certain action. Our formulation allows for different types of social interaction (ranging from sharing of information to direct adoption externalities) and also allows for the player to have incomplete information concerning the connections among individuals. The analysis starts by showing that incorporating information on social interaction can have large effects on the profits of a player. We then show that an increase in the level and dispersion of social interaction can raise or lower the optimal strategy and profits of the player, depending on the content of the interaction. We then study the value of social network information for the player and find that it depends on the dispersion in social connections. The economic interest of these results is illustrated via a discussion of two economic applications: advertising in the presence of word of mouth communication and seeding a network.

This article examines the hypothesis that group size is inversely related to successful collective action. A distinctive aspect of the article is that it combines the analysis of primary data collected by the authors with a game-theoretic model. The model considers a group of people protecting a commonly owned resource from excessive exploitation. The authors view monitoring of individual actions as a collective good and focus on third-party monitoring. We argue that the costs of monitoring rise more than proportionately as group size increases. This factor along with lumpiness in the monitoring technology yields the following theoretical conclusion: Medium-sized groups are more likely than small or large groups to provide third-party monitoring. The authors find that the empirical evidence is consistent with this theoretical result.