| Signal Detection from Social Media Interest1 #701135 This project aims to extract features or signals from social media text that are relevant to disease outbreak and at the same time identifying fake signals. We will apply natural language processing techniques, such as linguistic feature extraction, event detection, and deep neural network-based feature extraction, to identify potential signals for disease outbreak. We will investigate machine learning methods for predicting disease outbreak given the identified signals or features. |
- Co-Project Investigators: Aijun An, Jude Dzevela Kong and Manos Papagelis (York University)
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