SciDisruptor-PubMed

Description

Research hypothesis and data interpretation This project is based on the hypothesis that patterns of disruption in scientific publications can be identified in a fully automated and reproducible way through citation networks and the Disruption Index. To test this, a series of Python scripts was developed to extract, organize, and analyze data directly from the PubMed database. What the code demonstrates The scripts automate the entire process: (1) querying articles by keyword using the PubMed E-utilities API; (2) extracting complete article data in XML format; (3) cleaning and organizing the extracted data; (4) building the citation network among the selected articles; and (5) calculating the Disruption Index using the formula proposed by Wu, Wang, and Evans, via the PySciSci package. How to interpret and use the code Each script is modular and designed to run sequentially, with comments and instructions for execution in a Jupyter Notebook environment. Input data is retrieved directly from PubMed, and the outputs include: PMIDs of all articles, structured citation networks, tables with the count of citation types (A, B, C), and the final Disruption Index score. The code can be used by other researchers to replicate this study or to apply the pipeline to other scientific domains.

Steps to reproduce

The data were generated using Python scripts that automate the entire workflow—from querying PubMed to calculating the Disruption Index. The repository includes five main scripts: (1) retrieval of PMIDs using PubMed’s E-utilities API; (2) extraction of complete article data in XML format; (3) organization and cleaning of the extracted data; (4) construction of the citation network among articles; and (5) calculation of the Disruption Index using the PySciSci package. All scripts are reproducible, well-documented, and were executed in a Jupyter Notebook environment.

Institutions

• Universidade Federal de Juiz de Fora

  MG, Juiz de Fora

Categories

Funders

• Coordenação de Aperfeicoamento de Pessoal de Nível Superior

  Federal District, Brazil
• Fundação de Amparo à Pesquisa do Estado de Minas Gerais

  Minas Gerais, Brazil

Licence