Bibliometric Laws Toolkit

A toolkit to examine Laws of Bibliometrics based on bibliometric data

Installation

pip install biblio-laws

Functions

1. Examine the laws of bibliometrics, namely, Bradford's Law, Lotka's Law, and Zipf's Law.
2. Provide an easy tool to estimate parameters from the proposed formula of the laws.

Examples

Examine sample data distributions

from bibliolaws.datasets import *
from bibliolaws.zipf_law import ZipfLaw
from bibliolaws.bradford_law import BradfordLaw
from bibliolaws.lotka_law import LotkaLaw

# (1) Bradford's Law for relationship between journal and publication numbers
bf=BradfordLaw(load_bradford_sample_data())
bf.zone_analysis()
x,y=bf.figure_analysis()

# (2) Lotka's Law for relationship between author and publications numbers
lotka=LotkaLaw(load_lotka_sample_data())
lotka.print_table()
lotka.plot()

# (3) Zipf's Law for relationship between term rank and term freq.
zipf=ZipfLaw(load_zipf_sample_data())
zipf.print_table()
zipf.plot()

Screenshot of results

1. Bradford's Law

2. Lotka's Law

3. Zipf's Law

License

The biblio-laws project is provided by Donghua Chen.