Non-Parametric Scan Statistics for Disease Outbreak Detection on Twitter

Authors

  • Feng Chen Event and Pattern Detection Laboratory, Carnegie Mellon University, Pittsburgh, PA, United States
  • Daniel B. Neill Event and Pattern Detection Laboratory, Carnegie Mellon University, Pittsburgh, PA, United States

DOI:

https://doi.org/10.5210/ojphi.v6i1.5137

Abstract

We present a new method for disease outbreak detection, the "Non-Parametric Heterogeneous Graph Scan (NPHGS)". NPHGS enables fast and accurate detection of emerging space-time clusters using Twitter and other social media streams where standard parametric model assumptions are incorrect.

Author Biography

Feng Chen, Event and Pattern Detection Laboratory, Carnegie Mellon University, Pittsburgh, PA, United States

Feng Chen is currently a postdoctoral research fellow in Carnegie Mellon University.

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Published

2014-03-09

How to Cite

Chen, F., & Neill, D. B. (2014). Non-Parametric Scan Statistics for Disease Outbreak Detection on Twitter. Online Journal of Public Health Informatics, 6(1). https://doi.org/10.5210/ojphi.v6i1.5137

Issue

Section

Oral Presentations