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Presented by: Thomas Otto (Manager Business Intelligence)
Dr. Mehnaz Adnan (Senior Scientist Health Intelligence) Institute of Environmental Science & Research Ltd.
Credits:ESR – Dr. Mehnaz Adnan: Health Intelligence Analytics on Tweets ESR - Franco Andrews: SAP Data Integration, Modelling, Analytics and VisualisationESR IT: Infrastructure / FirewallSoltius NZ - Erik Roelofs: Connection Module and SAP Data Services
Syndromic Surveillance of Social Media - Big Data Analytics
Problem statement and hypothesis• Individuals disclose a lot of personal information on Social Media
channels (i.e. Facebook, Twitter etc.)
• There’s lots of Social Media Data (SMD) out there and:-• It is very noisy • It is not verified • It needs to be curated (checked by a clinician)
• Personal information contains location, names and self diagnosed syndromes
• SMD could be used to feed an early warning surveillance system
1. How to exploit twitter for public health monitoring (http://goo.gl/sOx9xo)
2. Digital disease detection—harnessing the Web for public health surveillance. (http://goo.gl/fxwoJT)
3. Influenza forecasting with Google flu trends. (http://goo.gl/z7GZco)
Related work
1) Denecke, K., Krieck, M., Otrusina, L., Smrz, P., Dolog, P., Nejdl, W., & Velasco, E. (2013). How to exploit twitter for public health monitoring. Methods Inf Med, 52(4), 326-339.
2) Brownstein, J. S., Freifeld, C. C., & Madoff, L. C. (2009). Digital disease detection—harnessing the Web for public health surveillance. New England Journal of Medicine, 360(21), 2153-2157.
3) Dugas, A. F., Jalalpour, M., Gel, Y., Levin, S., Torcaso, F., Igusa, T., & Rothman, R. E. (2013). Influenza forecasting with Google flu trends. PloS one, 8(2), e56176.
What is Social Media?Social media refers to the means of interactions among people in which they create, share, and/or exchange information and ideas in virtual communities and networks¹.
1 Tufts university, Boston, U.S.A.2 Social Media Examiner: 2014 Social Media Marketing Industry Report
Enrich Twitter data set with other, verified data (counts, location, time).
Verify withHealth Stats data
Verify with Lab Information Data
Verify with Sentinel data
Verify with National SurveillanceDatabase
PRONature scientific journal: There is a close correlation between the rates of doctor visits for flu symptoms, and the use of flu-like search terms. NZ Herald 23/7/14
CONResearchers from Harvard University state: Google Flu Tracker has overestimated for 100 of the 108 weeks starting from August, 2011 source: motherboard.vice.com
VISION - Big Data complements traditional methods Calibrate social media data with verified and trusted data to identify valid tweets
Risk Opportunity
• Social Media Data is validated and a trusted source of information
• Maybe used for indicative, early warnings of potential outbreaks?
Presented by: Thomas Otto (Manager Business Intelligence)
Dr. Mehnaz Adnan (Senior Scientist Health Intelligence) Institute of Environmental Science & Research Ltd.
Credits:ESR – Dr. Mehnaz Adnan: Health Intelligence Analytics on Tweets ESR - Franco Andrews: SAP Data Integration, Modelling, Analytics and VisualisationESR IT: Infrastructure / FirewallSoltius NZ - Erik Roelofs: Connection Module and SAP Data Services
Syndromic Surveillance of Social Media - Big Data Analytics