On the limited memory BFGS method for large scale optimization
Mathematical Programming: Series A and B
Language models for financial news recommendation
Proceedings of the ninth international conference on Information and knowledge management
Information extraction for enhanced access to disease outbreak reports
Journal of Biomedical Informatics - Special issue: Sublanguage
The predictive power of online chatter
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Bioinformatics
The third PASCAL recognizing textual entailment challenge
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Towards detecting influenza epidemics by analyzing Twitter messages
Proceedings of the First Workshop on Social Media Analytics
A demographic analysis of online sentiment during hurricane Irene
LSM '12 Proceedings of the Second Workshop on Language in Social Media
Mr. Scan: extreme scale density-based clustering using a tree-based network of GPGPU nodes
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
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We analyze over 570 million Twitter messages from an eight month period and find that tracking a small number of keywords allows us to estimate influenza rates and alcohol sales volume with high accuracy. We validate our approach against government statistics and find strong correlations with influenza-like illnesses reported by the U.S. Centers for Disease Control and Prevention (r(14) = .964, p r(5) = .932, p