Did You Really Just Have a Heart Attack? Towards Robust Detection of Personal Health Mentions in Social Media
Table 2. F1-measure for the models across all the topics in PHM2017 dataset.
['[BOLD] Model', '[BOLD] Alzheimer’s', '[BOLD] Heart attack', '[BOLD] Parkinson’s', '[BOLD] Cancer', '[BOLD] Depression', '[BOLD] Stroke']
The experiments show that our model WESPAD outperforms all the baselines in the majority of the topics. The substantial difference in terms of F1-measure between ME+lex and WESPAD models, shows that our model has successfully managed to learn the characteristics of the small set of the positive tweets, and to generalize better. We can also see that CNN, although with small amount of training data, is working surprisingly well. On the other hand, the complex LSTM+GRNN model is outperformed on all the topics by our WESPAD classifier.