@文章{信息:doi/10.2196/32378，作者="Chen, Emily和Jiang, Julie和Chang, Ho-Chun Herbert和Muric, Goran和Ferrara, Emilio"，标题="绘制信息和错误信息景观，以描述社交媒体上的错误信息:行星尺度上的COVID-19信息流行病学研究"，期刊="JMIR信息流行病学"，年="2022"，月="2"，日="8"，卷="2"，数="1"，页数="e32378"，关键词="社交媒体;社交网络;推特;COVID-19;有关;misinfodemics;infodemiology;背景:自2020年初以来，新型冠状病毒，也被称为SARS-CoV-2，已经开始定义我们的大部分生活。在此期间，世界各国都采取了封锁和保持社交距离的措施。人们的身体活动逐渐停止，而他们的在线互动随着他们转向彼此的虚拟互动而增加。 As the means of communication shifted online, information consumption also shifted online. Governing authorities and health agencies have intentionally shifted their focus to use social media and online platforms to spread factual and timely information. However, this has also opened the gate for misinformation, contributing to and accelerating the phenomenon of misinfodemics. Objective: We carried out an analysis of Twitter discourse on over 1 billion tweets related to COVID-19 over a year to identify and investigate prevalent misinformation narratives and trends. We also aimed to describe the Twitter audience that is more susceptible to health-related misinformation and the network mechanisms driving misinfodemics. Methods: We leveraged a data set that we collected and made public, which contained over 1 billion tweets related to COVID-19 between January 2020 and April 2021. We created a subset of this larger data set by isolating tweets that included URLs with domains that had been identified by Media Bias/Fact Check as being prone to questionable and misinformation content. By leveraging clustering and topic modeling techniques, we identified major narratives, including health misinformation and conspiracies, which were present within this subset of tweets. Results: Our focus was on a subset of 12,689,165 tweets that we determined were representative of COVID-19 misinformation narratives in our full data set. When analyzing tweets that shared content from domains known to be questionable or that promoted misinformation, we found that a few key misinformation narratives emerged about hydroxychloroquine and alternative medicines, US officials and governing agencies, and COVID-19 prevention measures. We further analyzed the misinformation retweet network and found that users who shared both questionable and conspiracy-related content were clustered more closely in the network than others, supporting the hypothesis that echo chambers can contribute to the spread of health misinfodemics. Conclusions: We presented a summary and analysis of the major misinformation discourse surrounding COVID-19 and those who promoted and engaged with it. While misinformation is not limited to social media platforms, we hope that our insights, particularly pertaining to health-related emergencies, will help pave the way for computational infodemiology to inform health surveillance and interventions. ", issn="2564-1891", doi="10.2196/32378", url="https://infodemiology.www.mybigtv.com/2022/1/e32378", url="https://doi.org/10.2196/32378", url="http://www.ncbi.nlm.nih.gov/pubmed/35190798" }