Assessing behavioral stages from social media data

Jason Liu, Elissa R. Weitzman, Rumi Chunara

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

Abstract

Important work rooted in psychological theory posits that health behavior change occurs through a series of discrete stages. Our work builds on the field of social computing by identifying how social media data can be used to resolve behavior stages at high resolution (e.g. hourly/daily) for key population subgroups and times. In essence this approach opens new opportunities to advance psychological theories and better understand how our health is shaped based on the real, dynamic, and rapid actions we make every day. To do so, we bring together domain knowledge and machine learning methods to form a hierarchical classification of Twitter data that resolves different stages of behavior. We identify and examine temporal patterns of the identified stages, with alcohol as a use case (planning or looking to drink, currently drinking, and reflecting on drinking). Known seasonal trends are compared with findings from our methods. We discuss the potential health policy implications of detecting high frequency behavior stages.

Original languageEnglish (US)
Title of host publicationCSCW 2017 - Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing
PublisherAssociation for Computing Machinery
Pages1320-1333
Number of pages14
ISBN (Electronic)9781450343350
DOIs
StatePublished - Feb 25 2017
Event2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2017 - Portland, United States
Duration: Feb 25 2017Mar 1 2017

Publication series

NameProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW

Other

Other2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2017
CountryUnited States
CityPortland
Period2/25/173/1/17

Keywords

  • Behavior
  • Health
  • Hierarchical classification
  • Natural language processing
  • Social media

ASJC Scopus subject areas

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

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  • Cite this

    Liu, J., Weitzman, E. R., & Chunara, R. (2017). Assessing behavioral stages from social media data. In CSCW 2017 - Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (pp. 1320-1333). (Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW). Association for Computing Machinery. https://doi.org/10.1145/2998181.2998336