#Coronavirus on TikTok: user engagement with misinformation as a potential threat to public health behavior.

IF 2.5 Q2 HEALTH CARE SCIENCES & SERVICES
Jonathan D Baghdadi, K C Coffey, Rachael Belcher, James Frisbie, Naeemul Hassan, Danielle Sim, Rena D Malik
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引用次数: 3

Abstract

Coronavirus disease (COVID)-related misinformation is prevalent online, including on social media. The purpose of this study was to explore factors associated with user engagement with COVID-related misinformation on the social media platform, TikTok. A sample of TikTok videos associated with the hashtag #coronavirus was downloaded on September 20, 2020. Misinformation was evaluated on a scale (low, medium, and high) using a codebook developed by experts in infectious diseases. Multivariable modeling was used to evaluate factors associated with number of views and presence of user comments indicating intention to change behavior. One hundred and sixty-six TikTok videos were identified and reviewed. Moderate misinformation was present in 36 (22%) videos viewed a median of 6.8 million times (interquartile range [IQR] 3.6-16 million), and high-level misinformation was present in 11 (7%) videos viewed a median of 9.4 million times (IQR 5.1-18 million). After controlling for characteristics and content, videos containing moderate misinformation were less likely to generate a user response indicating intended behavior change. By contrast, videos containing high-level misinformation were less likely to be viewed but demonstrated a nonsignificant trend towards higher engagement among viewers. COVID-related misinformation is less frequently viewed on TikTok but more likely to engage viewers. Public health authorities can combat misinformation on social media by posting informative content of their own.

Abstract Image

抖音上的冠状病毒:用户参与错误信息是对公共卫生行为的潜在威胁。
与新冠肺炎相关的错误信息在包括社交媒体在内的网络上普遍存在。本研究的目的是探索社交媒体平台TikTok上与covid相关的错误信息的用户参与度相关的因素。与#冠状病毒标签相关的抖音视频样本于2020年9月20日被下载。使用传染病专家开发的密码本对错误信息进行了评分(低、中、高)。使用多变量建模来评估与显示改变行为意图的用户评论数量和存在相关的因素。166个TikTok视频被识别并审查。中度错误信息出现在36个(22%)视频中,观看次数中位数为680万次(四分位数范围[IQR] 360 - 1600万),高度错误信息出现在11个(7%)视频中,观看次数中位数为940万次(IQR为510 - 1800万)。在控制了特征和内容之后,包含适度错误信息的视频不太可能产生表明预期行为改变的用户响应。相比之下,包含高度错误信息的视频不太可能被观看,但在观看者中显示出更高参与度的不显著趋势。在TikTok上,与新冠病毒相关的错误信息被看到的频率较低,但更有可能吸引观众。公共卫生当局可以通过发布自己的信息内容来打击社交媒体上的错误信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JAMIA Open
JAMIA Open Medicine-Health Informatics
CiteScore
4.10
自引率
4.80%
发文量
102
审稿时长
16 weeks
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