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Towards early discovery of salient health threats: a social media emotion classification technique

conference contribution
posted on 2016-01-01, 00:00 authored by Bahadorreza OfoghiBahadorreza Ofoghi, M Meghan, K Verspoor
Online social media microblogs may be a valuable resource for timely identification of critical ad hoc health-related incidents or serious epidemic outbreaks. In this paper, we explore emotion classification of Twitter microblogs related to localized public health threats, and study whether the public mood can be effectively utilized in early discovery or alarming of such events. We analyse user tweets around recent incidents of Ebola, finding differences in the expression of emotions in tweets posted prior to and after the incidents have emerged. We also analyse differences in the nature of the tweets in the immediately affected area as compared to areas remote to the events. The results of this analysis suggest that emotions in social media microblogging data (from Twitter in particular) may be utilized effectively as a source of evidence for disease outbreak detection and monitoring.

History

Event

Institute for Computational Biology. Symposium (21st : 2016 : Kohala Coast, Hawaii)

Series

Institute for Computational Biology Symposium

Pagination

504 - 515

Publisher

World Scientific Publishing

Location

Kohala Coast, Hawaii

Place of publication

Singapore

Start date

2016-01-04

End date

2016-01-08

ISBN-13

978-981-4749-41-1

Language

eng

Publication classification

E1.1 Full written paper - refereed; E Conference publication

Copyright notice

2016, World Scientific Publishing

Editor/Contributor(s)

R Altman, A Dunker, L Hunter, M Ritchie, T Murray, T Klein

Title of proceedings

PSB 2016 : Proceedings of Pacific Symposium on Biocomputing 2016