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.