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On infectious intestinal disease surveillance using social media content

Zou, B; Lampos, V; Gorton, R; Cox, IJ; (2016) On infectious intestinal disease surveillance using social media content. In: Kostkova, P and Grasso, F and Castillo, C, (eds.) DH '16: Proceedings of the 6th International Conference on Digital Health. (pp. pp. 157-161). Association for Computing Machinery (ACM): New York, NY, USA. Green open access

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Abstract

This paper investigates whether infectious intestinal diseases (IIDs) can be detected and quantified using social media content. Experiments are conducted on user-generated data from the microblogging service, Twitter. Evaluation is based on the comparison with the number of IID cases reported by traditional health surveillance methods. We employ a deep learning approach for creating a topical vocabulary, and then apply a regularised linear (Elastic Net) as well as a nonlinear (Gaussian Process) regression function for inference. We show that like previous text regression tasks, the nonlinear approach performs better. In general, our experimental results, both in terms of predictive performance and semantic interpretation, indicate that Twitter data contain a signal that could be strong enough to complement conventional methods for IID surveillance.

Type: Proceedings paper
Title: On infectious intestinal disease surveillance using social media content
Event: 6th International Conference on Digital Health (DH '16)
ISBN-13: 9781450342247
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/2896338.2896372
Publisher version: http://dx.doi.org/10.1145/2896338.2896372
Language: English
Additional information: Copyright © International World Wide Web Conference Committee (IW3C2) 2016.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Inst for Risk and Disaster Reduction
URI: https://discovery.ucl.ac.uk/id/eprint/1476028
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