  Keywords in scientific articles have found their significance in information
filtering and classification. In this article, we empirically investigated
statistical characteristics and evolutionary properties of keywords in a very
famous journal, namely Proceedings of the National Academy of Science of the
United States of America (PNAS), including frequency distribution, temporal
scaling behavior, and decay factor. The empirical results indicate that the
keyword frequency in PNAS approximately follows a Zipf's law with exponent
0.86. In addition, there is a power-low correlation between the cumulative
number of distinct keywords and the cumulative number of keyword occurrences.
Extensive empirical analysis on some other journals' data is also presented,
with decaying trends of most popular keywords being monitored. Interestingly,
top journals from various subjects share very similar decaying tendency, while
the journals of low impact factors exhibit completely different behavior. Those
empirical characters may shed some light on the in-depth understanding of
semantic evolutionary behaviors. In addition, the analysis of keyword-based
system is helpful for the design of corresponding recommender systems.
