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Never-Ending Learning
TLDR
The Never-Ending Language Learner is described, which achieves some of the desired properties of a never-ending learner, and lessons learned are discussed. Expand
Toward Real-Time Infoveillance of Twitter Health Messages.
TLDR
Qualitative considerations for human coding of Twitter data include coder selection and training, data representation, codebook development and refinement, and monitoring coding accuracy and productivity, are illustrated. Expand
World Vaping Day: Contextualizing Vaping Culture in Online Social Media Using a Mixed Methods Approach
Few studies have demonstrated the use of mixed methods research to contextualize health topics using primary data from social media. To address this gap in the methodological literature, we presentExpand
Machine Learning Classifiers for Twitter Surveillance of Vaping: Comparative Machine Learning Study
TLDR
Traditional and deep learning classifiers such as LSTM-CNN had superior performance and had the added advantage of requiring no preprocessing as well as supporting the development of a vaping surveillance system. Expand
Machine Learning Classifiers for Twitter Surveillance of Vaping: Comparative Machine Learning Study (Preprint)
BACKGROUND Twitter presents a valuable and relevant social media platform to study the prevalence of information and sentiment on vaping that may be useful for public health surveillance. MachineExpand