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Mathematical Underpinnings of AnalyticsTheory and Applications$
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Peter Grindrod

Print publication date: 2014

Print ISBN-13: 9780198725091

Published to Oxford Scholarship Online: March 2015

DOI: 10.1093/acprof:oso/9780198725091.001.0001

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Structure and responsiveness

Structure and responsiveness

Chapter:
(p.83) 3 Structure and responsiveness
Source:
Mathematical Underpinnings of Analytics
Author(s):

Peter Grindrod CBE

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198725091.003.0004

This chapter considers what dynamical models might tell about what has and has not been observed. This includes dynamics of opinions and social contacts which are time dependent and fully coupled. It considers Turing instability as a mechanism for generating patchiness in population models with both activator and inhibitory mechanisms as well as homophily. It considers how external events may drive avalanches of activity on peer-to-peer networks and also the possible exploitation of topic/interest-defined subsets of networks. It presents applications of Twitter data analysis in real time situations and to strategic decision-making in marketing.

Keywords:   Twitter networks, fully coupled networks, activator-inhibitor systems, homophily, turing instabilities, transient influencers, event driven activity spikes, bootstrap sampling, embedding, Bayes factors

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