Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/31841
Title: Marketing a Banned Remedy: A Topic Model Analysis of Health Misinformation in Thai E-Commerce
Authors: Suriyapaiboonwattana, K
Jaroenruen, Y
Satjawisate, S
Hone, K
Puttarak, P
Kaewboonma, N
Lertkrai, P
Nantapichai, S
Keywords: health misinformation;regulatory compliance;topic modeling;digital platforms;Thailand
Issue Date: 18-Aug-2025
Publisher: MDPI
Citation: Suriyapaiboonwattana, K. et al. (2025) 'Marketing a Banned Remedy: A Topic Model Analysis of Health Misinformation in Thai E-Commerce', Informatics, 12 (3), 84, pp. 1 - 25. doi: 10.3390/informatics12030084.
Abstract: Unregulated herbal products marketed via digital platforms present escalating risks to consumer safety and regulatory effectiveness worldwide. This study positions the case of Jindamanee herbal powder—a banned substance under Thai law—as a lens through which to examine broader challenges in digital health governance. Drawing on a dataset of 1546 product listings across major platforms (Facebook, TikTok, Shopee, and Lazada), we applied Latent Dirichlet Allocation (LDA) to identify prevailing promotional themes and compliance gaps. Despite explicit platform policies, 87.6% of listings appeared on Facebook. Medical claims, particularly for pain relief, featured in 77.6% of posts, while only 18.4% included any risk disclosure. These findings suggest a systematic exploitation of regulatory blind spots and consumer health anxieties, facilitated by templated cross-platform messaging. Anchored in Information Manipulation Theory and the Health Belief Model, the analysis offers theoretical insight into how misinformation is structured and sustained within digital commerce ecosystems. The Thai case highlights urgent implications for platform accountability, policy harmonization, and the design of algorithmic surveillance systems in global health product regulation.
Description: Data Availability Statement: The data used in this study consist of publicly available advertisements collected from social media and e-commerce platforms. No proprietary or personal data was collected. Relevant data or details about the data collection process are available from the corresponding author upon reasonable request.
URI: https://bura.brunel.ac.uk/handle/2438/31841
DOI: https://doi.org/10.3390/informatics12030084
Other Identifiers: ORCiD: Yuttana Jaroenruen https://orcid.org/0000-0001-6547-5662
ORCiD: Kate Hone https://orcid.org/0000-0001-5394-8354
ORCiD: Panupong Puttarak https://orcid.org/0000-0003-2534-5956
ORCiD: Nattapong Kaewboonma https://orcid.org/0000-0002-8207-7145
ORCiD: Puriwat Lertkrai https://orcid.org/0009-0005-5421-1334
Article number: 84
Appears in Collections:Dept of Computer Science Research Papers

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