Multiple opinions, including many that are negative, are produced in emergency events. These opinions are commonly formed asynchronously based on misinformation. However, most researches on opinion dynamics involving information neglect the asynchronous process of initial opinion formation due to information diffusion. Since online social networks like Sina Weibo act as major avenues for the expression, after analysing online behaviours, an opinion dynamic model is developed with consideration of misinformation diffusion of public opinion. In this model, schemes are developed for opinion interactions in multiple dimensions by introducing characteristics of online communication as another way of opinion interactions besides communication between neighbours. Subsequently, we investigate the impacts of network structure, diffusion rate, repost rate and other factors, which provide insights into understanding online opinion dynamics during emergency events. Furthermore, we conduct simulations to determine the intervention effects of different official responses. Results show that removing comments compulsively exhibits better performance in reducing negative opinion as well as increasing the density of Spreaders. Debunking misinformation by posting early results officially which indicates the probability of the existence of misinformation may lead public opinion in time if it takes a long time to finally confirm the misinformation.

在紧急事件中会产生多种意见，包括许多负面意见。这些意见通常是基于错误信息异步形成的。然而，大多数涉及信息的意见动态研究忽略了由于信息扩散导致的初始意见形成的异步过程。由于新浪微博等在线社交网络是表达的主要途径，在分析在线行为后，建立了一个考虑舆论错误信息传播的意见动态模型。在该模型中，通过引入在线交流的特点作为邻居之间交流之外的另一种意见互动方式，为多维度的意见互动开发了方案。随后，我们研究了网络结构、扩散速率、转发率和其他因素，这些因素有助于深入了解紧急事件期间的在线意见动态。此外，我们进行模拟以确定不​​同官方回应的干预效果。结果表明，强制删除评论在减少负面意见以及增加传播者密度方面表现出更好的性能。通过官方发布早期结果来揭穿错误信息，表明错误信息存在的可能性，如果需要很长时间才能最终确认错误信息，可能会及时引导舆论。结果表明，强制删除评论在减少负面意见以及增加传播者密度方面表现出更好的性能。通过官方发布早期结果来揭穿错误信息，表明错误信息存在的可能性，如果需要很长时间才能最终确认错误信息，可能会及时引导舆论。结果表明，强制删除评论在减少负面意见以及增加传播者密度方面表现出更好的性能。通过官方发布早期结果来揭穿错误信息，表明错误信息存在的可能性，如果需要很长时间才能最终确认错误信息，可能会及时引导舆论。