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Understanding and Diagnosing Antimicrobial Resistance on Social Media: A Yearlong Overview of Data and Analytics

机译:了解和诊断社交媒体的抗微生物抵抗:一岁的数据和分析概述

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摘要

To better understand user conversations revolving around antibiotics and antimicrobial resistance (AMR) on Twitter, we used an online data collection and analysis toolkit with full firehose access to collect corpuses of tweets with antibiotic and antimicrobial resistance keyword tracks. The date range included tweets from November 28, 2015, to November 25, 2016, for both datasets. This yearlong date range provides insight into how users have discussed antibiotics and AMR and identifies any spikes in activity during a particular time frame. Overall, we found that discussions about antibiotics and AMR predominantly occur in the United States and the United Kingdom, with roughly equal gender participation. These conversations are influenced by news sources, health professionals, and governmental health organizations. Users will often defer to retweet and recirculate content posted from these official sources and link to external articles instead of posting their own musings on the subjects. Our findings are important benchmarks in understanding the prevalence and reach of potential misinformation about antibiotics and AMR on Twitter.
机译:为了更好地了解围绕抗生素和抗微生物抵抗(AMR)在Twitter上旋转的用户对话,我们使用了在线数据收集和分析工具包,并具有充分的Firehose访问,以收集抗生素和抗微生物电阻关键字轨道的推文的核心。日期范围包括从2015年11月28日到2016年11月25日的推文,适用于两个数据集。这一年的日期范围提供了深入了解用户如何讨论抗生素和AMR,并在特定时间框架期间识别活动中的任何尖峰。总体而言,我们发现关于抗生素和AMR的讨论主要发生在美国和英国,具有大致平等的性别参与。这些谈话受到新闻来源,卫生专业人士和政府卫生组织的影响。用户通常会推迟到这些官方来源发布的转发和再循环内容,并链接到外部文章,而不是向受试者发布自己的博物员。我们的研究结果是了解患有关于抗生素和AMR在Twitter上的潜在错误信息的重要基准。

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