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Description

Our aim is to develop a multi-task convolutional neural network (MT-CNN) model to analyze public perceptions of measles from Twitter. We annotated a Twitter corpus relating to measles to train and evaluate our model. We compared the model to machine learning baselines and found its superiority. We further applied trained model on an un-labeled Twitter corpus collected from 2007 to 2019 and identified trends of public perceptions

Authors:

Samuel Wang (Presenter)
Clements High School

Jingcheng Du, UTHealth
Lu Tang, Texas A&M
Cui Tao, UTHealth

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