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Diffusion of innovations in dynamic networks

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  • Charlotte C. Greenan

Abstract

type="main" xml:id="rssa12054-abs-0001"> The evolution of a dynamic social network and the diffusion of an innovation are jointly modelled, dependent on one another, by using an extension of a stochastic actor-oriented model developed by Snijders, which is modified so that the adoption times follow a proportional hazards model. The asymptotic behaviour of the method-of-moments estimator is examined. The model is demonstrated on a data set involving the initiation of cannabis smoking among adolescents, and a simulation study is presented.

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  • Charlotte C. Greenan, 2015. "Diffusion of innovations in dynamic networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 147-166, January.
    • Handle: RePEc:bla:jorssa:v:178:y:2015:i:1:p:147-166
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    File URL: http://hdl.handle.net/10.1111/rssa.2014.178.issue-1
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    Cited by:

    1. Lindsay E. Young & John A. Schneider, 2021. "The Co-Evolution of Network Structure and PrEP Adoption among a Large Cohort of PrEP Peer Leaders: Implications for Intervention Evaluation and Community Capacity-Building," IJERPH, MDPI, vol. 18(11), pages 1-19, June.
    2. Young, Lindsay E. & Fujimoto, Kayo, 2021. "The Co-evolution of online social networks and syphilis incidence among young black men who have sex with men," Social Science & Medicine, Elsevier, vol. 272(C).
    3. Colin Gallagher & Dean Lusher & Johan Koskinen & Bopha Roden & Peng Wang & Aaron Gosling & Anastasios Polyzos & Martina Stenzel & Sarah Hegarty & Thomas Spurling & Gregory Simpson, 2023. "Network patterns of university-industry collaboration: A case study of the chemical sciences in Australia," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4559-4588, August.
    4. Verena Bauer & Dietmar Harhoff & Göran Kauermann, 2022. "A smooth dynamic network model for patent collaboration data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(1), pages 97-116, March.
    5. Matt Kammer-Kerwick & Mayra Yundt-Pacheco & Nayan Vashisht & Kara Takasaki & Noel Busch-Armendariz, 2023. "A Framework to Develop Interventions to Address Labor Exploitation and Trafficking: Integration of Behavioral and Decision Science within a Case Study of Day Laborers," Societies, MDPI, vol. 13(4), pages 1-31, April.
    6. Dutta, Amitava & Puvvala, Abhinay & Roy, Rahul & Seetharaman, Priya, 2017. "Technology diffusion: Shift happens — The case of iOS and Android handsets," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 28-43.
    7. Prasanta Bhattacharya & Tuan Q. Phan & Xue Bai & Edoardo M. Airoldi, 2019. "A Coevolution Model of Network Structure and User Behavior: The Case of Content Generation in Online Social Networks," Service Science, INFORMS, vol. 30(1), pages 117-132, March.
    8. Pink, Sebastian & Kretschmer, David & Leszczensky, Lars, 2020. "Choice modelling in social networks using stochastic actor-oriented models," Journal of choice modelling, Elsevier, vol. 34(C).
    9. Valente, Thomas W. & Dyal, Stephanie R. & Chu, Kar-Hai & Wipfli, Heather & Fujimoto, Kayo, 2015. "Diffusion of innovations theory applied to global tobacco control treaty ratification," Social Science & Medicine, Elsevier, vol. 145(C), pages 89-97.

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