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 T opic-aware C ommunity-level P hysical Activity Propagation with T emporal 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.

中文翻译：

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健康社交网络中具有时间动态的主题感知身体活动传播


对体力活动传播（例如活动水平和强度）进行建模是防止肥胖在社区中蔓延以及帮助在社交网络中传播健康和健康行为的关键。然而，还没有足够的科学和定量研究来阐明社交沟通如何提供身体活动干预。在这项工作中，我们引入了一种名为“主题感知社区级身体活动传播与时间动力学”（TCPT）的新颖模型，以分析不同粒度（即个人层面和社区层面）的身体活动传播和社会影响。给定一个社交网络，TCPT 模型首先整合社交传播内容、社交影响和时间动态之间的相关性。然后，利用分层方法来检测一组社区及其体育活动的相互影响强度。实验评估不仅显示了我们方法的有效性，还显示了检测到的社区与各种健康结果指标的相关性。我们令人鼓舞的结果为健康社交网络中的知识发现铺平了道路。