A Mixed-Methods Analysis of Women’s Health Misinformation on Social Media

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Abstract

Propelled by the COVID-19 pandemic and recent overturning of Roe vs. Wade in the United States [21], concerns have grown around the proliferation of reproductive health misinformation online. While a body of work in HCI has explored female health and wellbeing from a socio-technical perspective, a knowledge gap relating to women’s health misinformation and how it presents on social media remains. We report a mixed-methods content analysis of the ideological rhetoric, sources, and claims present in a sample of 202 officially fact-checked posts relating to female reproductive health. We found that reproductive health misinformation is diverse in its sources and represents a range of ideological standpoints, including pro-choice, feminist, and anti-authority rhetoric. We also found that claims are often tacit in nature, and rely on subtle manipulation and exaggerations to convey misleading narratives, as opposed to complete fabrications. In sum, we present a timely and nuanced analysis of the women’s health misinformation ecosystem. Our findings may inform priorities for HCI interventions that abate health misinformation, and more broadly, support women in navigating a complex and polarised information landscape.

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APA

Malki, L. M., Patel, D., & Singh, A. (2023). A Mixed-Methods Analysis of Women’s Health Misinformation on Social Media. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 14144 LNCS, pp. 419–428). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-42286-7_22

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