pybiblionet 1.0.0

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 TestPyPI:

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