The Diffusion of Innovations in Social Networks

By H. Peyton Young, Larry Blume, Steven N. Durlauf, Dean Phillips Foster, Stephen Morris. 2000

298 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/3a804610fe1ad0cfe3e04c1f0dcdb1339e9ca3c0

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In Management Science and Operations Research

In Statistical and Nonlinear Physics

Citations in the corpus

A framework for quantitative analysis of cascades on networks (2010, methodology): “Using these models, researchers have tried to infer global properties of information cascades in social networks [23, 9], devise eﬃ-cient methods to infer the underlying network structure [13, 11] or maximize cascade size [22, 21], and identify inﬂuential spreaders [14].”
Social ties and their relevance to churn in mobile telecom networks (2008, background): “With the web growing, much social network data is available and recent efforts try to leverage social ties for expertise location [15], viral marketing [7,16,27], and online social networking sites [2,18].”
Journal of Experimental & Theoretical Artificial Intelligence (2014, unknown): “…ow nl oa de d by [ D uk e U ni ve rs ity M ed ic al C en te r] a t 1 6: 56 0 1 Ja nu ar y 20 15 include adopting new technology (Rogers, 2003) and the diffusion of innovations in social networks (Acemoglu, Ozdaglar, & Yildiz, 2012; Keller-Schmidt & Klemm, 2012; Valente, 1996; Young, 2006).”
Maximizing the spread of influence through a social network (2003, background): “[5, 15, 18, 19, 21, 25, 28, 29, 31, 32, 33])but the following Linear Threshold Model lies at the core of most subsequent generalizations.”
Influence and correlation in social networks (2008, background): “There has already been significant research on methods for designing strategies to leverage social influence in such systems [3] and on the effect of influence on the growth pattern of new products [8].”
The Structure and Function of Complex Networks (2003, background): “The motivation behind studies of spin models on networks is usually either that they can be regarded as simple models of opinion formation in social networks [426] or that they provide general insight into the effects of network topology on phase transition processes.”
Can Network Theory-Based Targeting Increase Technology Adoption? (2018, unknown): “Acemoglu et al. (2011) highlights that when contagion is complex, highly clustered communities will need a seed placed in the community in order to induce adoption.”
Microblogging after a major disaster in China: a case study of the 2010 Yushu earthquake (2011, background): “Several models attempted to characterize the information diffusion process [1,6,28].”
Influential Nodes in a Diffusion Model for Social Networks (2005, background): “The linear threshold model has been the foundation for a large body of work in sociology; see, e.g., [8, 16, 17, 18, 19, 20, 21 ]; its generalization was introduced in [6].”