[Objective] This paper studies the features of h-degree in recommendation network of academic blogs. [Methods] Based on the datasets of blogs in ScienceNet.cn in 2013, construct the recommendation network of academic blogs, calculate the h-degree and related measures, and enter discussion by information visualization. [Results] In recommendation network of academic blogs, the generation of nodes with high h-degree is not only caused by academic knowledge connotations which are held by the information source (bloggers), but also because of the interest from topic the information source provided. This paper explores an approximate functional relationship (NA=b×hA2) between h-degree (hA) and node weighted degree (NA). Nodes with high h-degree typically become the organizer of subgroup in the center of a network. [Limitations] H-degree is not a perfect indicator, and the future studies will expand the improved h-degree. [Conclusions] H-degree can be one of the measurements for recommendation network analysis of academic blogs, and h-degree is also important for community management of this kind community.
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