Understanding the Social Mechanism of Cancer Misinformation Spread on YouTube and Lessons Learned: Infodemiological Study

BackgroundA knowledge gap exists between the list of required actions and the action plan for countering cancer misinformation on social media. Little attention has been paid to a social media strategy for disseminating factual information while also disrupting misinformation...

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Main Authors: Ho Young Yoon, Kyung Han You, Jung Hye Kwon, Jung Sun Kim, Sun Young Rha, Yoon Jung Chang, Sang-Cheol Lee
Format: Article
Language:English
Published: JMIR Publications 2022-11-01
Series:Journal of Medical Internet Research
Online Access:https://www.jmir.org/2022/11/e39571
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author Ho Young Yoon
Kyung Han You
Jung Hye Kwon
Jung Sun Kim
Sun Young Rha
Yoon Jung Chang
Sang-Cheol Lee
author_facet Ho Young Yoon
Kyung Han You
Jung Hye Kwon
Jung Sun Kim
Sun Young Rha
Yoon Jung Chang
Sang-Cheol Lee
author_sort Ho Young Yoon
collection DOAJ
description BackgroundA knowledge gap exists between the list of required actions and the action plan for countering cancer misinformation on social media. Little attention has been paid to a social media strategy for disseminating factual information while also disrupting misinformation on social media networks. ObjectiveThe aim of this study was to, first, identify the spread structure of cancer misinformation on YouTube. We asked the question, “How do YouTube videos play an important role in spreading information about the self-administration of anthelmintics for dogs as a cancer medicine for humans?” Second, the study aimed to suggest an action strategy for disrupting misinformation diffusion on YouTube by exploiting the network logic of YouTube information flow and the recommendation system. We asked the question, “What would be a feasible and effective strategy to block cancer misinformation diffusion on YouTube?” MethodsThe study used the YouTube case of the self-administration of anthelmintics for dogs as an alternative cancer medicine in South Korea. We gathered Korean YouTube videos about the self-administration of fenbendazole. Using the YouTube application programming interface for the query “fenbendazole,” 702 videos from 227 channels were compiled. Then, videos with at least 50,000 views, uploaded between September 2019 and September 2020, were selected from the collection, resulting in 90 videos. Finally, 10 recommended videos for each of the 90 videos were compiled, totaling 573 videos. Social network visualization for the recommended videos was used to identify three intervention strategies for disrupting the YouTube misinformation network. ResultsThe study found evidence of complex contagion by human and machine recommendation systems. By exposing stakeholders to multiple information sources on fenbendazole self-administration and by linking them through a recommendation algorithm, YouTube has become the perfect infrastructure for reinforcing the belief that fenbendazole can cure cancer, despite government warnings about the risks and dangers of self-administration. ConclusionsHealth authorities should upload pertinent information through multiple channels and should exploit the existing YouTube recommendation algorithm to disrupt the misinformation network. Considering the viewing habits of patients and caregivers, the direct use of YouTube hospital channels is more effective than the indirect use of YouTube news media channels or government channels that report public announcements and statements. Reinforcing through multiple channels is the key.
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spelling doaj.art-5e735afc1d7246d08b2c1bc37caaffe22023-08-28T23:16:38ZengJMIR PublicationsJournal of Medical Internet Research1438-88712022-11-012411e3957110.2196/39571Understanding the Social Mechanism of Cancer Misinformation Spread on YouTube and Lessons Learned: Infodemiological StudyHo Young Yoonhttps://orcid.org/0000-0002-5307-1967Kyung Han Youhttps://orcid.org/0000-0001-9498-8504Jung Hye Kwonhttps://orcid.org/0000-0002-5965-3204Jung Sun Kimhttps://orcid.org/0000-0003-1132-5217Sun Young Rhahttps://orcid.org/0000-0002-2512-4531Yoon Jung Changhttps://orcid.org/0000-0001-7750-4213Sang-Cheol Leehttps://orcid.org/0000-0003-0139-9909 BackgroundA knowledge gap exists between the list of required actions and the action plan for countering cancer misinformation on social media. Little attention has been paid to a social media strategy for disseminating factual information while also disrupting misinformation on social media networks. ObjectiveThe aim of this study was to, first, identify the spread structure of cancer misinformation on YouTube. We asked the question, “How do YouTube videos play an important role in spreading information about the self-administration of anthelmintics for dogs as a cancer medicine for humans?” Second, the study aimed to suggest an action strategy for disrupting misinformation diffusion on YouTube by exploiting the network logic of YouTube information flow and the recommendation system. We asked the question, “What would be a feasible and effective strategy to block cancer misinformation diffusion on YouTube?” MethodsThe study used the YouTube case of the self-administration of anthelmintics for dogs as an alternative cancer medicine in South Korea. We gathered Korean YouTube videos about the self-administration of fenbendazole. Using the YouTube application programming interface for the query “fenbendazole,” 702 videos from 227 channels were compiled. Then, videos with at least 50,000 views, uploaded between September 2019 and September 2020, were selected from the collection, resulting in 90 videos. Finally, 10 recommended videos for each of the 90 videos were compiled, totaling 573 videos. Social network visualization for the recommended videos was used to identify three intervention strategies for disrupting the YouTube misinformation network. ResultsThe study found evidence of complex contagion by human and machine recommendation systems. By exposing stakeholders to multiple information sources on fenbendazole self-administration and by linking them through a recommendation algorithm, YouTube has become the perfect infrastructure for reinforcing the belief that fenbendazole can cure cancer, despite government warnings about the risks and dangers of self-administration. ConclusionsHealth authorities should upload pertinent information through multiple channels and should exploit the existing YouTube recommendation algorithm to disrupt the misinformation network. Considering the viewing habits of patients and caregivers, the direct use of YouTube hospital channels is more effective than the indirect use of YouTube news media channels or government channels that report public announcements and statements. Reinforcing through multiple channels is the key.https://www.jmir.org/2022/11/e39571
spellingShingle Ho Young Yoon
Kyung Han You
Jung Hye Kwon
Jung Sun Kim
Sun Young Rha
Yoon Jung Chang
Sang-Cheol Lee
Understanding the Social Mechanism of Cancer Misinformation Spread on YouTube and Lessons Learned: Infodemiological Study
Journal of Medical Internet Research
title Understanding the Social Mechanism of Cancer Misinformation Spread on YouTube and Lessons Learned: Infodemiological Study
title_full Understanding the Social Mechanism of Cancer Misinformation Spread on YouTube and Lessons Learned: Infodemiological Study
title_fullStr Understanding the Social Mechanism of Cancer Misinformation Spread on YouTube and Lessons Learned: Infodemiological Study
title_full_unstemmed Understanding the Social Mechanism of Cancer Misinformation Spread on YouTube and Lessons Learned: Infodemiological Study
title_short Understanding the Social Mechanism of Cancer Misinformation Spread on YouTube and Lessons Learned: Infodemiological Study
title_sort understanding the social mechanism of cancer misinformation spread on youtube and lessons learned infodemiological study
url https://www.jmir.org/2022/11/e39571
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