This article investigates the performance of models on social media posts by examining different Transformer architectures. It evaluates the effectiveness of fine-tuning and prompt-based methods, aiming to identify best practices and trade-offs through performance comparisons across various models.
Topic modeling, particularly with advanced tools like BERTopic, presents a promising approach for extracting insights into SDoH from unstructured text.