Pain, both physical and emotional, is a fundamental human experience categorized as acute or chronic. While research has explored its causes and treatments across disciplines, the influence of gender has often been overlooked in earlier studies. In this study, we utilized Natural Language Processing (NLP) to analyze and gain deeper insights into individuals’ pain experiences, with a particular focus on gender differences. We successfully classified posts into male and female corpora using the Hidden Attribute Model-Convolutional Neural Network (HAM-CNN), achieving an F1 score of 0.86 by aggregating posts based on usernames. Our analysis found that female posts were more emotionally focused, with conditions like migraine and sinusitis more common among women. It also revealed gender-based differences in responses to pain medication.