Presentation + Paper
6 June 2024 The impact of misinformation on the health of underrepresented youth during public health crises: a preliminary study
Author Affiliations +
Abstract
The widespread misinformation in the digital age has emerged as a significant societal challenge with far-reaching implications. While concerns about the threats of misinformation on the mental health of individuals have garnered attention, there remains a critical gap in our understanding of how misinformation uniquely affects the young generation, particularly those belonging to underrepresented groups. Emerging evidence suggests that underrepresented groups among the young generation, including marginalized communities, ethnic minorities, and socioeconomically disadvantaged individuals, often face heightened vulnerabilities to the harmful effects of misinformation. These groups encounter a unique intersection of social, economic, and cultural factors, exacerbating their susceptibility to false or harmful information. Understanding the differential impacts of misinformation within these communities is vital for creating targeted interventions and support mechanisms. With a long-term goal of offering a thorough understanding of the current state of knowledge in this critical area, this paper reports a preliminary literature review examining how false information about vaccines spreads on social media, creating a huge problem called an “infodemic” and revealing how misinformation against vaccines gets shared in social media and why people believe them. In addition, a small-scale case study is conducted based on the dataset collected by the team.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Lulu Al Arfaj, Joon Suk Lee, Joseph A. Shelton, Zeynep Ertem, Thi Tran, and Yu Chen "The impact of misinformation on the health of underrepresented youth during public health crises: a preliminary study", Proc. SPIE 13058, Disruptive Technologies in Information Sciences VIII, 130580Y (6 June 2024); https://doi.org/10.1117/12.3013295
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KEYWORDS
COVID 19

Web 2.0 technologies

Analytical research

Data analysis

Social networks

Communication theory

Machine learning

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