Preprint
Beyond Binary Detection: A Multi-Dimensional Taxonomy of Cancer Misinformation on Reddit
ArXiv.org
14 Jul 2026
Abstract
Cancer-related discussions on social media provide an important space for information exchange and peer support, but also facilitate the spread of misinformation that may influence prevention, screening, and treatment decisions. Existing research on cancer misinformation often relies on narrow definitions, small-scale datasets, or binary labeling frameworks. We introduce a multi-dimensional taxonomy for characterizing cancer misinformation in Reddit discussions of breast, lung, colon, and prostate cancer. The taxonomy captures seven dimensions, including misinformation presence, information type, risk level, stance, and topical focus. Using expert-annotated data, we evaluate multiple large language models (LLMs) for scalable misinformation annotation and analyze cancer misinformation across Reddit communities. Our results show that cancer-related misinformation constitutes approximately 6% of Reddit cancer discussions, with substantial variation across communities and misinformation topics. Few-shot prompting substantially improves classification performance, particularly for nuanced taxonomy dimensions. We additionally identify recurring misinformation narratives centered on unsupported treatments, distrust of conventional medicine, and misleading claims about diagnosis and screening. Our taxonomy, dataset, and findings provide a foundation for multi-dimensional modeling of online cancer misinformation.
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Details
- Title
- Beyond Binary Detection: A Multi-Dimensional Taxonomy of Cancer Misinformation on Reddit
- Creators
- Aria Pessianzadeh - Drexel UniversityPooriya Jamie - University of California, Los AngelesNaima Sultana - Drexel UniversityGeorgia Himmelstein - University of California, Los AngelesYuliya Zektser - University of California, Los AngelesPatricia Ganz - University of California, Los AngelesHoma Hosseinmardi - University of California, Los AngelesAmir Ghasemian - University of California, Los AngelesRezvaneh Rezapour - Drexel University
- Publication Details
- ArXiv.org
- Resource Type
- Preprint
- Language
- English
- Academic Unit
- Information Science
- Other Identifier
- 991022197046004721