An Adaptive Network Model for the Changes in Human Behaviour in Response to the Spread of COVID-19

Sharmayne Soh, Shihan Yu, Jan Treur*

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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Abstract

The aim of the study reported here was to develop a model that can simulate the changes in human behaviour in response to the COVID-19 outbreak. To achieve this, a second-order adaptive social network model was designed integrating mental network models for each person. The model is based on adaptation principles such as the first-order Hebbian learning adaptation principle and the second-order ‘adaptation accelerates with increasing exposure’ adaptation principle.

Original languageEnglish
Title of host publicationData Science and Intelligent Systems
Subtitle of host publicationProceedings of 5th Computational Methods in Systems and Software 2021, Vol. 2
EditorsRadek Silhavy, Petr Silhavy, Zdenka Prokopova
PublisherSpringer Science and Business Media Deutschland GmbH
Pages932-946
Number of pages15
Volume2
ISBN (Electronic)9783030903213
ISBN (Print)9783030903206
DOIs
Publication statusPublished - 2021
Event5th Computational Methods in Systems and Software, CoMeSySo 2021 - Virtual, Online
Duration: 1 Oct 20211 Oct 2021

Publication series

NameLecture Notes in Networks and Systems
PublisherSpringer
Volume231 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference5th Computational Methods in Systems and Software, CoMeSySo 2021
CityVirtual, Online
Period1/10/211/10/21

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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