Workshop Proceedings of the 19th International AAAI Conference on Web and Social Media
Workshop: #SMM4H-HeaRD 2025: Joint 10th Social Media Mining for Health and Health Real-World Data Workshop and Shared Tasks
DOI: 10.36190/2025.77We present the BrynMawr NLP System for the 10th Social Media Mining for Health Research and Applications Workshop (SMM4H 2025), addressing Task 6 - distinguishing Reddit posts that contain personal mentions of adverse reactions to herpes zoster (shingles) vaccines from other vaccine-related discussions. Our system is based on a simple logistic regression model trained on the predictions from a fine-tuned RoBERTa model and Naive Bayes model. We explore stacking a fine-tuned RoBERTa model with traditional non-neural models to improve upon just fine-tuning a pre-trained RoBERTA model. Our experiments demonstrate that statistical, non-neural models perform well on this dataset but their performance do not compare with those of a fine-tuned Transformer.