Using a Temporal-Causal Network Model for Computational Analysis of the Effect of Social Media Influencers on the Worldwide Interest in Veganism

Manon Lisa Sijm, Chelsea Rome Exel*, Jan Treur

*Corresponding author for this work

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

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Abstract

Over the years, a clear and steady rise can be seen in the interest in veganism. Although research has been conducted to determine the reasons why veganism has grown, ultimately there is still a necessity for further research on how social networks affect its growth. This paper aims to provide a possible explanation for the rise in interest, using computational analysis based on a temporal-causal network model focussing on social contagion. This model portrays a simulation of a sample size population on Instagram, showing how a social influencer can influence the opinions of people directly (influencers’ followers) and indirectly (followers of the influencers’ followers), and how this compares to a situation in which this influencer is not there.

Original languageEnglish
Title of host publication4th International Congress on Information and Communication Technology - ICICT 2019, London
EditorsXin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
PublisherSpringer
Pages129-140
Number of pages12
Volume2
ISBN (Electronic)9789813293434
ISBN (Print)9789813293427
DOIs
Publication statusPublished - 2020
Event4th International Congress on Information and Communication Technology, ICICT 2019 - London, United Kingdom
Duration: 27 Feb 201928 Feb 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1027
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference4th International Congress on Information and Communication Technology, ICICT 2019
CountryUnited Kingdom
CityLondon
Period27/02/1928/02/19

Keywords

  • Network-oriental modelling approach
  • Social contagion
  • Social media
  • Temporal-causal network
  • Veganism

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