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Applying GIS and Machine Learning Methods to Twitter Data for Multiscale Surveillance of Influenza
- Source :
- PLoS ONE, PLoS ONE, Vol 11, Iss 7, p e0157734 (2016)
- Publication Year :
- 2016
- Publisher :
- Public Library of Science, 2016.
-
Abstract
- Traditional methods for monitoring influenza are haphazard and lack fine-grained details regarding the spatial and temporal dynamics of outbreaks. Twitter gives researchers and public health officials an opportunity to examine the spread of influenza in real-time and at multiple geographical scales. In this paper, we introduce an improved framework for monitoring influenza outbreaks using the social media platform Twitter. Relying upon techniques from geographic information science (GIS) and data mining, Twitter messages were collected, filtered, and analyzed for the thirty most populated cities in the United States during the 2013-2014 flu season. The results of this procedure are compared with national, regional, and local flu outbreak reports, revealing a statistically significant correlation between the two data sources. The main contribution of this paper is to introduce a comprehensive data mining process that enhances previous attempts to accurately identify tweets related to influenza. Additionally, geographical information systems allow us to target, filter, and normalize Twitter messages.
- Subjects :
- Viral Diseases
Geographic information system
020205 medical informatics
Computer science
lcsh:Medicine
Social Sciences
02 engineering and technology
Filter (software)
Disease Outbreaks
Machine Learning
0302 clinical medicine
Public health surveillance
Sociology
Geoinformatics
0202 electrical engineering, electronic engineering, information engineering
Information system
Medicine and Health Sciences
Public and Occupational Health
Public Health Surveillance
030212 general & internal medicine
Geography, Medical
lcsh:Science
Multidisciplinary
Geography
Applied Mathematics
Simulation and Modeling
Social Communication
3. Good health
Infectious Diseases
Social Networks
Physical Sciences
Network Analysis
Algorithms
Research Article
Computer and Information Sciences
Twitter
Research and Analysis Methods
03 medical and health sciences
Machine Learning Algorithms
Artificial Intelligence
Support Vector Machines
Influenza, Human
Flu season
Humans
Social media
business.industry
lcsh:R
Outbreak
Biology and Life Sciences
Data science
Communications
Influenza
United States
Geographic Information Systems
Earth Sciences
Cognitive Science
lcsh:Q
business
Social Media
Mathematics
Neuroscience
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 11
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....10a686a0d8c81e5d7d4cb6d2bb06f535