Filtered States: Active Inference, Social Media and Mental Health

Ben White, Mark Miller

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

Abstract

Social media is implicated today in an array of mental health concerns. While worries around social media have become mainstream, little is known about the specific cognitive mechanisms underlying the correlations seen in these studies, or why we find it so hard to stop engaging with these platforms when things obviously begin to deteriorate for us. New advances in computational neuroscience are now perfectly poised to shed light on this matter. In this paper we approach these concerns around social media and mental health issues, including the troubling rise in Snapchat surgeries, depression and addiction, through the lens of the Active Inference Framework (AIF).

Original languageEnglish
Title of host publicationMachine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Proceedings
PublisherSpringer
Pages772-783
Number of pages12
ISBN (Print)9783030937355
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event21st European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2021 - Virtual, Online
Duration: 13 Sept 202117 Sept 2021

Publication series

NameCommunications in Computer and Information Science
Volume1524 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference21st European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2021
CityVirtual, Online
Period13/09/2117/09/21

Keywords

  • Active inference
  • Addiction
  • Depression
  • Social media

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