The rapid development of online social media causes, we can share any kind of information with very fast. The information can be positive or negative. The negative news that will create many issues in our society. Negative information may be rumor or misinformation. So that it is necessary to block the propagation these type of rumors in social media. In this paper we focus on the reducing dynamic rumour influence with considering the user expertise. Here our aim is that reduce the number of users who accept these rumor. So that we using the Ising model to define rumor propagation in online social media. Also we are considering constraint of user experience utility. If the block time of each user exceeds that threshold, the utility of the network will decrease. Considering this constraint, formulate survival theory. Experiments area unit implemented supported large-scale world networks and validate the effectiveness of our methodology.