https://doi.org/10.1140/epjb/e2008-00453-9
Empirical analysis on a keyword-based semantic system
1
Department of Physics, University of Fribourg, Chemin du Musée 3, 1700 Fribourg, Switzerland
2
Department of Modern Physics, University of Science and Technology of China, 230026, Hefei Anhui, P.R. China
Corresponding author: a zhutou@ustc.edu
Received:
22
June
2008
Revised:
18
October
2008
Published online:
12
December
2008
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.
PACS: 89.75.-k – Complex systems / 05.65.+b – Self-organized systems / 05.10.-a – Computational methods in statistical physics and nonlinear dynamics
© EDP Sciences, Società Italiana di Fisica, Springer-Verlag, 2008