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The Speed of Innovation Diffusion in Social Networks
Author(s) -
Arieli Itai,
Babichenko Yakov,
Peretz Ron,
Young H. Peyton
Publication year - 2020
Publication title -
econometrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 16.7
H-Index - 199
eISSN - 1468-0262
pISSN - 0012-9682
DOI - 10.3982/ecta17007
Subject(s) - status quo , upper and lower bounds , network topology , diffusion , function (biology) , topology (electrical circuits) , social network (sociolinguistics) , population , mathematical economics , innovation diffusion , computer science , microeconomics , mathematics , economics , combinatorics , sociology , computer network , physics , market economy , social media , demography , knowledge management , mathematical analysis , evolutionary biology , biology , world wide web , thermodynamics
New ways of doing things often get started through the actions of a few innovators, then diffuse rapidly as more and more people come into contact with prior adopters in their social network. Much of the literature focuses on the speed of diffusion as a function of the network topology. In practice, the topology may not be known with any precision, and it is constantly in flux as links are formed and severed. Here, we establish an upper bound on the expected waiting time until a given proportion of the population has adopted that holds independently of the network structure. Kreindler and Young (2014) demonstrated such a bound for regular networks when agents choose between two options: the innovation and the status quo. Our bound holds for directed and undirected networks of arbitrary size and degree distribution, and for multiple competing innovations with different payoffs.