TY -的盟Fedoruk本杰明AU -纳尔逊,哈里森AU -弗罗斯特,罗素盟——Fucile Ladouceur, Kai PY - 2021 DA - 2021/12/21 TI -平民算法:一个民主的方法来审查和适度乔- Res JMIR形式SP - e32427六世- 5 - 12 KW - infodemiology KW -错误KW -算法KW -社会媒体KW -平民KW -自然语言处理KW -情绪分析KW -情绪KW -信任KW -决策KW - COVID-19 AB -背景:COVID-19大流行造成的信息大流行引发了若干社会问题，包括公众与卫生专家之间的不信任加剧，甚至一些人拒绝接受疫苗接种;有消息称，四分之一的美国人会拒绝接种疫苗。这种社会关注可以追溯到今天的数字化水平，尤其是社交媒体的形式。目的:本研究的目标是确定一种最优的社交媒体算法，该算法能够减少错误信息的数量，同时也能确保某些个人自由(如言论自由)得到维护。在完成本文所述的分析之后，抽象出一种算法。发现一组最优社交媒体算法的抽象方面是本研究的目的。方法:由于社交媒体是错误信息传播的最重要因素，该团队决定在各种基于文本的平台(Twitter、4chan、Reddit、Parler、Facebook和YouTube)上研究信息流行病学。这是通过情绪分析将一般帖子与被标记为错误信息的关键词语(所有这些词语都与COVID-19有关)进行比较，以确定其真实性。在收集数据集时，使用了应用程序编程接口(使用Python的pip安装)和由标准科学第三方编译的现有数据。 Results: The sentiment can be described using bimodal distributions for each platform, with a positive and negative peak, as well as a skewness. It was found that in some cases, misinforming posts can have up to 92.5% more negative sentiment skew compared to accurate posts. Conclusions: From this, the novel Plebeian Algorithm is proposed, which uses sentiment analysis and post popularity as metrics to flag a post as misinformation. This algorithm diverges from that of the status quo, as the Plebeian Algorithm uses a democratic process to detect and remove misinformation. A method was constructed in which content deemed as misinformation to be removed from the platform is determined by a randomly selected jury of anonymous users. This not only prevents these types of infodemics but also guarantees a more democratic way of using social media that is beneficial for repairing social trust and encouraging the public’s evidence-informed decision-making. SN - 2561-326X UR - https://formative.www.mybigtv.com/2021/12/e32427 UR - https://doi.org/10.2196/32427 UR - http://www.ncbi.nlm.nih.gov/pubmed/34854812 DO - 10.2196/32427 ID - info:doi/10.2196/32427 ER -