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Since the research hotspot development in academic fields is mainly reflected through academic journal contents, how to analyze the evolving action of academic journal related topics is a huge factor for researchers in grasping the tendency of research hotspots. This paper considered and combined two characteristics of academic journals: 1) topic property and 2) time-sequence feature to realize journals' time-sequence topic extraction, which also puts forward the TS-JTM (Time Sequence Journal Topic Model) at the same time. On the basis of TS-JTM, we developed topic-snapshot journal hotspot evolution model based on time sequence, and proposed a method which could detect the continuing, emerging, splitting, amalgamating or disappearing between two neighbor topic-snapshots, with adopting topic similarity measurement based on Kullback-Leibler (KL) Divergence. Our experiments show that the proposed method could realize evolving analysis of journals' research hotspots effectively.