  Academic papers have been the protagonists in disseminating expertise.
Naturally, paper citation pattern analysis is an efficient and essential way of
investigating the knowledge structure of science and technology. For decades,
it has been observed that citation of scientific literature follows a
heterogeneous and heavy-tailed distribution, and many of them suggest a
power-law distribution, log-normal distribution, and related distributions.
However, many studies are limited to small-scale approaches; therefore, it is
hard to generalize. To overcome this problem, we investigate 21 years of
citation evolution through a systematic analysis of the entire citation history
of 42,423,644 scientific literatures published from 1996 to 2016 and contained
in SCOPUS. We tested six candidate distributions for the scientific literature
in three distinct levels of Scimago Journal & Country Rank (SJR) classification
scheme. First, we observe that the raw number of annual citation acquisitions
tends to follow the log-normal distribution for all disciplines, except for the
first year of the publication. We also find significant disparity between the
yearly acquired citation number among the journals, which suggests that it is
essential to remove the citation surplus inherited from the prestige of the
journals. Our simple method for separating the citation preference of an
individual article from the inherited citation of the journals reveals an
unexpected regularity in the normalized annual acquisitions of citations across
the entire field of science. Specifically, the normalized annual citation
acquisitions have power-law probability distributions with an exponential
cut-off of the exponents around 2.3, regardless of its publication and citation
year. Our results imply that journal reputation has a substantial long-term
impact on the citation.
