Why do diffusion data not fit the logistic model? A note on network discreteness, heterogeneity and anisotropy

0Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Diffusion of innovations and knowledge is in most cases accounted for by the logistic model. Fieldwork research however constantly report that empirical data utterly deviate from this mathematical function. This chapter scrutinizes network forcing of diffusion process. The departure of empirical data from the logistic function is explained by social network discreteness, heterogeneity and anisotropy. New indices are proposed. Results arc illustrated by empirical data from an original study of knowledge diffusion in the medieval academic network. © 2010 Springer-Verlag Wien.

Cite

CITATION STYLE

APA

Raynaud, D. (2010). Why do diffusion data not fit the logistic model? A note on network discreteness, heterogeneity and anisotropy. In From Sociology to Computing in Social Networks: Theory, Foundations and Applications (pp. 215–230). Springer Vienna. https://doi.org/10.1007/978-3-7091-0294-7_12

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free