A tutorial on modeling and analysis of dynamic social networks. Part I

A survey on the fusion process in opinion dynamics

The promise (and pitfalls) of ICT for agriculture initiatives

In order to induce farmers to adopt a productive new agricultural technology, we apply simple and complex contagion diffusion models on rich social network data from 200 villages in Malawi to identify seed farmers to target and train on the new technology. A randomized controlled trial compares these theory-driven network targeting approaches to simpler strategies that either rely on a government extension worker or an easily measurable proxy for the social network (geographic distance between households) to identify seed farmers. Our results indicate that technology diffusion is characterized by a complex contagion learning environment in which most farmers need to learn from multiple people before they adopt themselves. Network theory based targeting can out-perform traditional approaches to extension, and we identify methods to realize these gains at low cost to policymakers. 
Keywords: Social Learning, Agricultural Technology Adoption, Complex Contagion, Malawi 
JEL Classification Codes: O16, O13

Can Network Theory-based Targeting Increase Technology Adoption?

The coordination and control of social systems is the foundational problem of sociology. The discipline was established in Europe in the aftermath of the American and French Revolutions. With the dismantling of the hierarchical controls of European aristocratic systems, the examination of alternative mechanisms of coordination and control became a preoccupation. The Industrial Revolution (c. 1760-1840), which was occurring at the same time, reinforced this preoccupation by decoupling the power of purse and the power of positions of authority. While the hierarchies of church and state retained coercive power, the exercise of such power was increasingly contested. The moral compass of society, its general welfare, and its capacity to adapt to changing circumstances appeared to be aggregated properties of the unconstrained opinions and behaviors of a large collectivity of individuals. The definition of the problem of coordination and control, which emerged in Europe in the new discipline of sociology, still resonates and guides current sociological work. The problem definition [1], broadly stated, is this: if value is placed on nonhierarchical mechanisms of social control, then what mechanisms and structures (consistent with this value) allow a coordination and control of social systems?

The Problem of Social Control and Coordination of Complex Systems in Sociology: A Look at the Community Cleavage Problem

We study binary opinion dynamics in a social network with stubborn agents who influence others but do not change their opinions. We focus on a generalization of the classical voter model by introducing nodes (stubborn agents) that have a fixed state. We show that the presence of stubborn agents with opposing opinions precludes convergence to consensus; instead, opinions converge in distribution with disagreement and fluctuations. In addition to the first moment of this distribution typically studied in the literature, we study the behavior of the second moment in terms of network properties and the opinions and locations of stubborn agents. We also study the problem of optimal placement of stubborn agents where the location of a fixed number of stubborn agents is chosen to have the maximum impact on the long-run expected opinions of agents.

Binary Opinion Dynamics with Stubborn Agents

While social networks do affect diffusion of innovations, the exact nature of these effects are far from clear, and, in many cases, there exist conflicting hypotheses among researchers. In this paper, we focus on the linear threshold model where each individual requires exposure to (potentially) multiple sources of adoption in her neighborhood before adopting the innovation herself. In contrast with the conclusions in the literature, our bounds suggest that innovations might spread further across networks with a smaller degree of clustering. We provide both analytical evidence and simulations for our claims. Finally, we propose an extension for the linear threshold model to better capture the notion of path dependence, i.e., a few minor shocks along the way could alter the course of diffusion significantly.

/pdf/diffusion-of-innovations-in-social-networks-3tlxtytbcd.pdf

Diffusion of innovations in social networks

Recent advances in information technology have allowed firms to gather vast amounts of data regarding consumers’ preferences and the structure and intensity of their social interactions. This paper examines a game-theoretic model of competition between firms that can target their marketing budgets to individuals embedded in a social network. We provide a sharp characterization of the optimal targeted advertising strategies and highlight their dependence on the underlying social network structure. Furthermore, we provide conditions under which it is optimal for the firms to asymmetrically target a subset of the individuals and establish a lower bound on the ratio of their payoffs in these asymmetric equilibria. Finally, we find that at equilibrium firms invest inefficiently high in targeted advertising and the extent of the inefficiency is increasing in the centralities of the agents they target. Taken together, these findings shed light on the effect of the network structure on the outcome of marketing co...

/pdf/competitive-targeted-advertising-over-networks-22m4exl7t7.pdf

Competitive Targeted Advertising Over Networks

Recent advances in information technology have allowed firms to gather vast amounts of data regarding consumers’ preferences and the structure and intensity of their social interactions. This paper examines a game-theoretic model of competition between firms which can target their marketing budgets to individuals embedded in a social network. We provide a sharp characterization of the optimal targeted marketing strategies and highlight their dependence on the underlying social network structure. Furthermore, we identify network structures for which the returns to targeting are maximized and we provide conditions under which it is optimal for the firms to asymmetrically target a subset of the individuals. Finally, we provide a lower bound on the extent of asymmetry in these asymmetric equilibria and therefore shed light on the effect of the network structure on the outcome of marketing competition between the firms.

Ercan Yildiz

Papers

Binary Opinion Dynamics with Stubborn Agents

Diffusion of innovations in social networks

Competitive Targeted Advertising Over Networks

Competing over Networks