TY - JOUR AU - Yin, AU - Shao傅莲，AU - Ji雪英，AU - Wu美琪，建宏PY - 2021 DA - 201/2/12 TI -量化COVID-19信息传播中意见传播延迟的影响:建模研究JO - J医学互联网Res SP - e25734 VL - 23is - 2kw - COVID-19 KW -延迟传输KW -动态模型KW -新浪微博KW -社交媒体KW -通信KW -在线健康信息KW -健康信息KW -公共卫生KW -意见KW -战略KW -模型KW -信息传输KW -延迟KW -信息监测AB -背景:在COVID-19大流行等快速演变的公共卫生危机中，可以在社交媒体平台上连续发布多条相关信息。后续发布次数之间的间隔可能会对新旧信息的传播和交叉传播产生不同的影响，从而导致新信息转发用户的峰值和最终规模不同，这取决于内容相关性以及新信息是在旧信息的爆发阶段发布还是在准稳态阶段发布。目的:本研究旨在帮助设计有效的传播策略，以确保信息传递给最大数量的用户。方法:建立并分析了两类具有延迟传播的易感免疫信息传播模型，以描述相关信息的交叉传播过程。每个意见领袖频繁发布的具有较高影响力的COVID-19相关典型信息共28661次转发(数据采集至2020年2月19日)。以10分钟为频率将信息处理成离散点，通过模型数值模拟对真实数据进行拟合。此外，还分析了参数对信息传播和出版策略设计的影响。结果:公众无法及时有效地浏览当前疫情、防疫等相关权威信息。 The ingenious use of information release intervals can effectively enhance the interaction between information and realize the effective diffusion of information. We parameterized our models using real data from Sina Microblog and used the parameterized models to define and evaluate mutual attractiveness indexes, and we used these indexes and parameter sensitivity analyses to inform optimal strategies for new information to be effectively propagated in the microblog. The results of the parameter analysis showed that using different attractiveness indexes as the key parameters can control the information transmission with different release intervals, so it is considered as a key link in the design of an information communication strategy. At the same time, the dynamic process of information was analyzed through index evaluation. Conclusions: Our model can carry out an accurate numerical simulation of information at different release intervals and achieve a dynamic evaluation of information transmission by constructing an indicator system so as to provide theoretical support and strategic suggestions for government decision making. This study optimizes information posting strategies to maximize communication efforts for delivering key public health messages to the public for better outcomes of public health emergency management. SN - 1438-8871 UR - //www.mybigtv.com/2021/2/e25734/ UR - https://doi.org/10.2196/25734 UR - http://www.ncbi.nlm.nih.gov/pubmed/33529153 DO - 10.2196/25734 ID - info:doi/10.2196/25734 ER -