A real-time architecture for detection of diseases using social networks: design, implementation and evaluation

Authors:
Mustafa Sofean;Matthew Smith
Affiliations:
University of Hannover, Hannover, Germany;University of Hannover, Hannover, Germany
Venue:
Proceedings of the 23rd ACM conference on Hypertext and social media
Year:
2012

Citing 1
Cited 0

Medical case-driven classification of microblogs: characteristics and annotation

Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium

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Abstract

In this work we developed a surveillance architecture to detect diseases-related postings in social networks using Twitter as an example for a high-traffic social network. Our real-time architecture uses Twitter streaming API to crawl Twitter messages as they are posted. Data mining techniques have been used to index, extract and classify postings. Finally, we evaluate the performance of the classifier with a dataset of public health postings and also evaluate the run-time performance of whole system with respect to latency and throughput.