Measuring the preferential attachment mechanism in citation networks

In this paper, we investigated the preferential attachment mechanism (PAM) by considering the dynamic property in papers’ in-degree k for three citation networks. We found that the past citations obtained in different years will have different influences on papers’ attachment rate Π(k,t). We proposed two methods to consider these different influences. One is the Gradually-vanishing Memory Preferential Attachment Mechanism (GMPAM) based on weighted past citations. The other is the Short-term Memory Preferential Attachment Mechanism (SMPAM) based on citations obtained in the recent one-year period. Experiments showed that SMPAM is simpler and more universal in practice. We can just calculate the citations to papers in the recent one-year period to study the papers’ attachment property.