Diffusion of innovations

Epidemiology of widgets

January 30, 2020 — February 9, 2023

adaptive
collective knowledge
economics
hidden variables
incentive mechanisms
institutions
mind
networks
social graph
sociology
technology
virality
wonk

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Models such as the Bass diffusion model impose an epidemiological structure on the contagion of products, with a survival analysis flavour. Or, if you’d like, memetics but for technical ideas rather than beliefs.

Figure 1

1 Incoming

  • Getting The Word Out—by Steven Johnson

    I wrote about the disappointing—though I suppose not surprising—lack of coverage of the death of Dilip Mahalanabis, the Bangladeshi doctor who played a critical role in popularising Oral Rehydration Therapy, the amazingly simple medical intervention that has saved millions of lives around the world over the past fifty years. I noted that as far as I could tell, no mainstream news organization outside of India had run so much as a brief obituary of Mahalanabis, despite the heroic nature of his initial adoption of ORT in the middle of a refugee crisis in the early 1970s, and the long-term legacy of his work. (The Lancet once called ORT “potentially the most important medical advance of the 20th century”.) …when we talk about the history of innovation, we often over-index on the inventors and underplay the critical role of popularizers, the people who are unusually gifted at making the case for adopting a new innovation, or who have a platform that gives them an unusual amount of influence.

2 References

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Bakshy, Rosenn, Marlow, et al. 2012. The Role of Social Networks in Information Diffusion.” In Proceedings of the 21st International Conference on World Wide Web. WWW ’12.
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———. 2004. Comments on ‘A New Product Growth for Model Consumer Durables The Bass Model’.” Management Science.
Bentley, Ormerod, and Batty. 2011. Evolving Social Influence in Large Populations.” Behavioral Ecology and Sociobiology.
Bentley, Ormerod, and Shennan. 2011. Population-Level Neutral Model Already Explains Linguistic Patterns.” Proceedings of the Royal Society B: Biological Sciences.
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Goel, Watts, and Goldstein. 2012. The Structure of Online Diffusion Networks.” In Proceedings of the 13th ACM Conference on Electronic Commerce - EC ’12.
Guidolin, and Manfredi. 2023. Innovation Diffusion Processes: Concepts, Models, and Predictions.” Annual Review of Statistics and Its Application.
Houghton. 2021. Interdependent Diffusion: The Social Contagion of Interacting Beliefs.” arXiv:2010.02188 [Physics].
Iribarren, and Moro. 2009. Impact of Human Activity Patterns on the Dynamics of Information Diffusion.” Physical Review Letters.
Meade, and Islam. 2006. “Modeling and Forecasting the Diffusion of Innovation - A 25 Year Review.” International Journal of Forecasting.
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Romero, Meeder, and Kleinberg. 2011. Differences in the Mechanics of Information Diffusion Across Topics: Idioms, Political Hashtags, and Complex Contagion on Twitter.” In Proceedings of the 20th International Conference on World Wide Web. WWW ’11.
Rossman. 2012. Climbing the Charts: What Radio Airplay Tells Us about the Diffusion of Innovation.
Sinha, and Chandrashekaran. 1992. A Split Hazard Model for Analyzing the Diffusion of Innovations.” Journal of Marketing Research.
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