The scale-free model for citation network

Preferential attachment mechanism (PAM) is considered to be one of the kernel ingredients in forming the scale-free topology of complex networks. In our previous work, we investigated the PAM for a typical real-world complex network-citation network by considering the dynamic citation properties in nodes´ in-degree. And the short-term preferential attachment mechanism (SMPAM) is proposed to explore the reason for forming the scale-free topology of citation network. Basing on SMPAM, we further proposed a scale-free network model for citation network. The model just considers the citations that papers obtained in the recent one-year period to determine the attachment rate. Taking the mean field method, we deduced the degree distribution of citation network and found that the model evolving into a scale-free network with the power-law exponent r=2. The results by simulation also show a good power-law distribution of citation network, which exhibits the validity of the model proposed.