Using publicly accessible Reddit posts, we developed a manually annotated dataset for traditional and aspect-based sentiment analysis (ABSA) of cannabis-related discussions in the context of pain management. The dataset consists of 479 post-aspect pairs extracted from specific Reddit communities associated with autoimmune rheumatic diseases (ARDs). We filtered posts using a structured list of cannabis-related terms and extracted context using rule-based sentence segmentation. Subsequently, we manually annotated each instance for both traditional and aspect-specific sentiment (positive, negative, neutral), achieving a final inter-annotator reliability of 0.79, indicating substantial agreement. The dataset offers valuable resources for training, benchmarking, and evaluating machine learning models for ABSA in health-related social media contexts. This dataset can support research in natural language processing, public health informatics, pain medicine, digital epidemiology, and social media-based health monitoring.