新浪微博中意见领袖意见传播延迟对COVID-19信息传播影响的量化研究
Quantify Influence of Delay in Opinion Transmission of Opinion Leaders on COVID-19 Information Propagation in the Chinese Sina-microblog
摘要：
在快速演变的重大公共卫生危机（如COVID-19疫情）中，多条相关信息可按顺序发布于社交媒体平台。后续发布时间之间的间隔可能对新旧信息的传输和交叉传播产生不同的影响，从而导致新信息的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还是准稳态阶段发布。为了帮助设计有效的通信策略，以确保信息被传递到最大数量的用户，我们开发和分析两类具有延迟传输的可靠-转发-免疫信息传播模型，以描述相关信息的交叉传播过程。我们使用新浪微博的真实数据对这些模型进行参数化，并使用参数化模型来定义和评估相互吸引力指数，我们使用这些指数和参数敏感性分析来告知策略，以确保新信息在微博中有效传播的最佳策略。
英文摘要：
In a fast evolving major public health crisis such as the COVID-19 pandemic, multiple pieces of relevant information can be posted sequentially in a social media platform. The interval between subsequent posting times may have different impact on the transmission and cross-propagation of the old and new information to result in different peak value and final size of forwarding users of the new information, depending on the content correlation and whether the new information is posted during the outbreak or quasi steady state phase of the old information. To help in designing effective communication strategies to ensure information is delivered to the maximal number of users, we develop and analyze two classes of susceptible-forwarding-immune information propagation models with delay in transmission, to describe the cross-propagation process of relevant information. We parametrize these models using real data from the Sina-Microblog and use the parametrized models to define and evaluate mutual attractiveness indices, and we use these indices and parameter sensitivity analyses to inform strategies to ensure optimal strategies for a new information to be effectively propagated in the microblog.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
