%0杂志文章%@ 2564-1891 %I JMIR出版物%V 2% 卡塔尔世界杯8强波胆分析N 1% P e32378 %T绘制信息和错误信息景观，以描述社交媒体上的错误信息:行星尺度的COVID-19信息流行病学研究% a Chen,Emily % a Jiang,Julie % a Chang,Ho-Chun Herbert % a Muric,Goran % a Ferrara,Emilio %+信息科学研究所，南加州大学，4676金钟路，1001号，Marina del Rey, CA, 90292，美国，1 310 448 8661，emiliofe@usc.edu %K社交媒体%K社交网络%K推特%K COVID-19 %K信息病学%K错误信息%K信息流行病学%K错误信息%D 2022 %7 8.2.2022 %9原始论文%J JMIR信息流行病学%G英语%X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。随着交流方式的网络化，信息消费也随之网络化。管理当局和卫生机构有意将重点转向利用社交媒体和在线平台传播真实和及时的信息。然而，这也为错误信息打开了大门，导致和加速了错误信息的现象。目的:我们对一年来与COVID-19有关的10多亿条推文的推文进行了分析，以确定和调查流行的错误信息叙述和趋势。我们还旨在描述更容易受到健康相关错误信息影响的Twitter受众，以及驱动错误信息传播的网络机制。 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. %M 35190798 %R 10.2196/32378 %U https://infodemiology.www.mybigtv.com/2022/1/e32378 %U https://doi.org/10.2196/32378 %U http://www.ncbi.nlm.nih.gov/pubmed/35190798