Microblog, with its good interaction and convenient dissemination, has become the main platform for public opinion dissemination. How to discover the law of public opinion dissemination, and to identify the public opinion accurately have become the hot researches. In this paper, we define the user influence, topic popularity, topic interest to analysis the process of opinions fusion among the users under the interest and confidence threshold. We propose a new public opinion evolution HK–SEIR model which combines the opinion fusion HK and the epidemic transmission SEIR models. Firstly, the topic interest degree is added to the opinion fusion HK model, and the interaction behavior between the users under the interest and confidence threshold is analyzed. Then, we calculate the probability of topic propagation caused by the interaction of opinions between users under group pressure, and the probability that users change from the infected state to the removed state under topic popularity. Finally, we analyze the changes of the susceptible, exposed, infected and removed states in the process of public opinion communication. The experiment proves that the HK–SEIR model is closer to the work-rest rules of public opinion communication than SEIR, SIR model. The density peak time is closer to the peak of real public opinion communication. We find that the user interest is the main factor influencing the public opinion dissemination after the interaction of user opinions fusion reaches a certain degree. The negative public opinion of the higher proportion can easily reach the peak of public opinion propagation.

微博互动性好，传播方便，已成为舆论传播的主要平台。如何发现舆论传播规律，准确地识别舆论已成为研究的热点。在本文中，我们定义了用户影响力，主题受欢迎度，主题兴趣，以分析在兴趣和置信度阈值下用户之间的意见融合过程。我们提出了一种新的舆论演化HK–SEIR模型，该模型结合了意见融合HK和流行病传播SEIR模型。首先，将主题兴趣度添加到意见融合HK模型中，分析了兴趣和置信度阈值下用户之间的交互行为。然后，我们计算了在小组压力下用户之间的意见交互导致的主题传播概率，以及在主题流行度下用户从受感染状态变为已移除状态的概率。最后，我们分析了舆论交流过程中易感，暴露，感染和被清除状态的变化。实验证明，与SEIR，SIR模型相比，HK-SEIR模型更接近于舆论传播的工作休息规则。密度高峰时间更接近真实舆论交流的高峰。在用户意见融合互动达到一定程度后，我们发现用户利益是影响舆论传播的主要因素。较高比例的负面舆论很容易达到舆论传播的顶峰。