Topic-aware physical activity propagation with temporal dynamics in a health social network

Nhathai Phan, Javid Ebrahimi, David Kil, Brigitte Piniewski, Dejing Dou

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Modeling physical activity propagation, such as activity level and intensity, is a key to preventing obesity from cascading through communities, and to helping spread wellness and healthy behavior in a social network. However, there have not been enough scientific and quantitative studies to elucidate how social communication may deliver physical activity interventions. In this work, we introduce a novel model named Topic-aware Community-level Physical Activity Propagation with Temporal Dynamics (TCPT) to analyze physical activity propagation and social influence at different granularities (i.e., individual level and community level). Given a social network, the TCPT model first integrates the correlations between the content of social communication, social influences, and temporal dynamics. Then, a hierarchical approach is utilized to detect a set of communities and their reciprocal influence strength of physical activities. The experimental evaluation shows not only the effectiveness of our approach but also the correlation of the detected communities with various health outcome measures. Our promising results pave a way for knowledge discovery in health social networks.

Original languageEnglish (US)
Article number2
JournalACM Transactions on Intelligent Systems and Technology
Volume8
Issue number1
DOIs
StatePublished - Aug 2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Artificial Intelligence

Keywords

  • Health social network
  • Physical activity propagation

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