Computational approaches toward integrating quantified self sensing and social media

Munmun De Choudhury, Mrinal Kumar, Ingmar Weber

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

The growing amount of data collected by quantified self tools and social media hold great potential for applications in personalized medicine. Whereas the first includes health-related physiological signals, the latter provides insights into a user's behavior. However, the two sources of data have largely been studied in isolation. We analyze public data from users who have chosen to connect their MyFitnessPal and Twitter accounts. We show that a user's diet compliance success, measured via their self-logged food diaries, can be predicted using features derived from social media: linguistic, activity, and social capital. We find that users with more positive affect and a larger social network are more successful in succeeding in their dietary goals. Using a Granger causality methodology, we also show that social media can help predict daily changes in diet compliance success or failure with an accuracy of 77%, that improves over baseline techniques by 17%. We discuss the implications of our work in the design of improved health interventions for behavior change.

Original languageEnglish
Title of host publicationCSCW 2017 - Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing
PublisherAssociation for Computing Machinery
Pages1334-1349
Number of pages16
ISBN (Electronic)9781450343350
DOIs
Publication statusPublished - 25 Feb 2017
Event2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2017 - Portland, United States
Duration: 25 Feb 20171 Mar 2017

Other

Other2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2017
CountryUnited States
CityPortland
Period25/2/171/3/17

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Keywords

  • Behavior change
  • Diet
  • Fitness
  • Health
  • MyFitnessPal
  • Quantified self
  • Social media
  • Twitter
  • Well-being

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Human-Computer Interaction

Cite this

De Choudhury, M., Kumar, M., & Weber, I. (2017). Computational approaches toward integrating quantified self sensing and social media. In CSCW 2017 - Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (pp. 1334-1349). Association for Computing Machinery. https://doi.org/10.1145/2998181.2998219