Local spatial obesity analysis and estimation using online social network sensors

Sun, Qindong; Wang, Nan; Li, Shancang; Zhou, Hongyi

Abstract

© 2018 Elsevier Inc. Recently, the online social networks (OSNs) have received considerable attentions as a revolutionary platform to offer users massive social interaction among users that enables users to be more involved in their own healthcare. The OSNs have also promoted increasing interests in the generation of analytical, data models in health informatics. This paper aims at developing an obesity identification, analysis, and estimation model, in which each individual user is regarded as an online social network ‘sensor’ that can provide valuable health information. The OSN-based obesity analytic model requires each sensor node in an OSN to provide associated features, including dietary habit, physical activity, integral/incidental emotions, and self-consciousness. Based on the detailed measurements on the correlation of obesity and proposed features, the OSN obesity analytic model is able to estimate the obesity rate in certain urban areas and the experimental results demonstrate a high success estimation rate. The measurements and estimation experimental findings created by the proposed obesity analytic model show that the online social networks could be used in analyzing the local spatial obesity problems effectively.

Citation

Sun, Q., Wang, N., Li, S., & Zhou, H. (2018). Local spatial obesity analysis and estimation using online social network sensors. Journal of Biomedical Informatics, 83, 54-62. https://doi.org/10.1016/j.jbi.2018.03.010

• Journal Article Type: Article
• Acceptance Date: Feb 18, 2018
• Online Publication Date: Mar 15, 2019
• Publication Date: Jul 1, 2018
• Deposit Date: Feb 27, 2018
• Publicly Available Date: Mar 15, 2019
• Journal: Journal of Biomedical Informatics
• Print ISSN: 1532-0464
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 83
• Pages: 54-62
• DOI: https://doi.org/10.1016/j.jbi.2018.03.010
• Keywords: online social networks, Internet of Things (IoT), obesity, health informatics, bioinformatics, public health
• Public URL: https://uwe-repository.worktribe.com/output/865389
• Publisher URL: https://doi.org/10.1016/j.jbi.2018.03.010