In order to identify subject research hotspots and cutting-edge topics accurately and effectively, choosing the Altmetrics Attention Score(AAS) value of the Altmetric.com platform, which is weighted synthesis of 17 indicators, to identify high-profile research topics based on the z-index. Articles of five excellent information science journals in 2018 selected from SSCI database as samples to obtain the AAS values of these papers. The citation frequencies in the z-index are replaced by AAS, and a zt index model was constructed to identify the research topics. The authors construct zt index model to identify high AAS attention research topics, and construct a mean baseline classification model to subdivide the recognition results. There are 16 high-interest research topics of information science were identified, and the research contents of four categories of potential, emerged, core, and marginal categories were subdivided. Research found that the zt index model and the topic classification model of high-concerned subject research constructed
in this paper are feasible and effective.