pybiblionet 1.0.5

PyBiblioNet is a Python library for performing network-based bibliometrics

PyBiblioNet

PyBiblioNet is a Python library for performing network-based bibliometrics, an analytical framework that leverages network science to study and quantify relationships and influence among scientific entities such as authors, and articles.

Why Use Network Analysis in Bibliometrics?

Network analysis provides powerful tools to uncover key patterns and actors in the scholarly ecosystem. By computing centrality metrics, it is possible to go beyond traditional indicators like raw citation counts or the h-index. Network-based metrics help identify:

• Influential authors or papers within and across research domains.
• Bridge entities that connect otherwise separated communities.
• Nodes that are highly connected to authoritative or prestigious sources.

These nuanced insights allow for a more refined understanding of scientific impact and visibility, as demonstrated in the literature (e.g., Diallo et al., 2016).

Features

• Easy modeling of citation and collaboration networks.
• Calculation of a wide variety of centrality and influence metrics.
• Integration with common network science libraries (e.g., networkx, igraph).
• Support for directed and weighted graphs.
• Ready-to-use functions for common bibliometric scenarios.

Installation

To install the latest version from Pypip (recommended) or TestPyPI:

pip install --upgrade pybiblionet

or

pip install --upgrade pybiblionet  --index-url https://test.pypi.org/simple/ pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple

This project uses spaCy for text processing and requires the English language model en_core_web_sm.
After installing the package, please download the model by running:

python -m spacy download en_core_web_sm

tested on Windows 11 with python 3.10 and visual studio code 2022 on linux (Ubuntu 24.04) with python 3.12 on mac OS (Ventura 13.2) with python 3.10

Bug Reports & Feedback

If you encounter any problems, the best way to reach me is by opening a new GitHub Issue. This helps keep everything transparent and trackable.