With the continuous growth of micro-blog services, Sina Weibo is increasingly found in the daily lives of ordinary Chinese individuals. More than one hundred million tweets are released in Sina Weibo everyday. By analyzing these mass data timely, media companies could learn how to generate buzz for new films, famous stars, or fashion shows more effectively. However, how to predict which topics will be the most popular search terms in Sina Weibo in realtime remains unknown. In this paper, we present a realtime hot topic prediction method in an online platform. Experiments are carried out on the platform to evaluate the proposed scheme. The results show that our model gets an average precision 44.32% and the median value is 45.83%. The proposed hot topic prediction method can predict the hot topics about 9.5 hours in average in advance.