Prediction of Population Health Indices from Social Media using Kernel-based Textual and Temporal Features

@article{Nguyen2017PredictionOP,
  title={Prediction of Population Health Indices from Social Media using Kernel-based Textual and Temporal Features},
  author={Thin Nguyen and Duc Thanh Nguyen and Mark Erik Larsen and Bridianne O’Dea and John Yearwood and Dinh Q. Phung and Svetha Venkatesh and Helen Christensen},
  journal={Proceedings of the 26th International Conference on World Wide Web Companion},
  year={2017}
}
From 1984, the US has annually conducted the Behavioral Risk Factor Surveillance System (BRFSS) surveys to capture either health behaviors, such as drinking or smoking, or health outcomes, including mental, physical, and generic health, of the population. [] Key Method The proposed textual features are defined at mid-level and can be applied on top of various low-level textual features.

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