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The Diffusion of Microfinance

TLDR
This article examined how participation in a micro-finance program diffuses through social networks and found that participants are significantly more likely to pass information on to friends and acquaintances than informed non-participants.
Abstract
We examine how participation in a microfinance program diffuses through social networks. We collected detailed demographic and social network data in 43 villages in South India before microfinance was introduced in those villages and then tracked eventual participation. We exploit exogenous variation in the importance (in a network sense) of the people who were first informed about the program, "the injection points". Microfinance participation is higher when the injection points have higher eigenvector centrality. We estimate structural models of diffusion that allow us to (i) determine the relative roles of basic information transmission versus other forms of peer influence, and (ii) distinguish information passing by participants and non-participants. We find that participants are significantly more likely to pass information on to friends and acquaintances than informed non-participants, but that information passing by non-participants is still substantial and significant, accounting for roughly a third of informedness and participation. We also find that, conditioned on being informed, an individual's decision is not significantly affected by the participation of her acquaintances.

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Generalized Spectral Clustering via Gromov-Wasserstein Learning

TL;DR: This work establishes a bridge between spectral clustering and Gromov-Wasserstein Learning (GWL), a recent optimal transport-based approach to graph partitioning, and shows that when comparing against a two-node template graph using the heat kernel at the infinite time limit, the resulting partition agrees with the partition produced by the Fiedler vector.
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TL;DR: The reported results shed light on the sensitivity of betweenness, closeness, and degree centrality metrics to fused graph inputs and the role of HVI identification as a test and evaluation tool for fusion process optimization.
Proceedings ArticleDOI

Improving Information Spread through a Scheduled Seeding Approach

TL;DR: This work revisits the problem of network seeding and demonstrates by simulations how an approach takes takes into account the timing aspect, can improve the rates of spread by over 23% compared to existing seeding methods.
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Understanding tie strength in social networks using a local "bow tie" framework.

TL;DR: The social bow tie framework is introduced, which consists of a focal tie and all actors connected to either or both of the two focal nodes on either side of the focal tie, to investigate associations between the strength of the “central” tie and properties of the bow tie.
ReportDOI

Naive Learning with Uninformed Agents

TL;DR: It is shown that an agent's social influence in this generalized DeGroot model is essentially proportional to the number of uninformed nodes who will hear about an event for the first time via this agent, which allows us to relate network geometry to information aggregation.
References
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Journal ArticleDOI

Collective dynamics of small-world networks

TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.

A Contribution to the Mathematical Theory of Epidemics.

TL;DR: The present communication discussion will be limited to the case in which all members of the community are initially equally susceptible to the disease, and it will be further assumed that complete immunity is conferred by a single infection.
Journal ArticleDOI

A Simple Model of Herd Behavior

TL;DR: In this article, the authors analyze a sequential decision model in which each decision maker looks at the decisions made by previous decision makers in taking her own decision, and they show that the decision rules that are chosen by optimizing individuals will be characterized by herd behavior.
Proceedings ArticleDOI

Maximizing the spread of influence through a social network

TL;DR: An analysis framework based on submodular functions shows that a natural greedy strategy obtains a solution that is provably within 63% of optimal for several classes of models, and suggests a general approach for reasoning about the performance guarantees of algorithms for these types of influence problems in social networks.
Journal ArticleDOI

Epidemic Spreading in Scale-Free Networks

TL;DR: A dynamical model for the spreading of infections on scale-free networks is defined, finding the absence of an epidemic threshold and its associated critical behavior and this new epidemiological framework rationalizes data of computer viruses and could help in the understanding of other spreading phenomena on communication and social networks.