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A graph-based approach for population health analysis using Geo-tagged tweets

journal contribution
posted on 2021-02-01, 00:00 authored by H Nguyen, Thin NguyenThin Nguyen, Duc Thanh NguyenDuc Thanh Nguyen
We propose in this work a graph-based approach for automatic public health analysis using social media. In our approach, graphs are created to model the interactions between features and between tweets in social media. We investigated different graph properties and methods in constructing graph-based representations for population health analysis. The proposed approach is applied in two case studies: (1) estimating health indices, and (2) classifying health situation of counties in the US. We evaluate our approach on a dataset including more than one billion tweets collected in three years 2014, 2015, and 2016, and the health surveys from the Behavioral Risk Factor Surveillance System. We conducted realistic and large-scale experiments on various textual features and graph-based representations. Experimental results verified the robustness of the proposed approach and its superiority over existing ones in both case studies, confirming the potential of graph-based approach for modeling interactions in social networks for population health analysis.

History

Journal

Multimedia tools and applications

Volume

80

Pagination

7187 - 7204

Publisher

Springer

Location

New York, N.Y.

ISSN

1380-7501

eISSN

1573-7721

Language

eng

Publication classification

C1 Refereed article in a scholarly journal