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scraping-google-scholar

https://github.com/guadag12/scraping-google-scholar

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
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    DOI references
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    Academic publication links
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    Academic email domains
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    Institutional organization owner
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (7.6%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: guadag12
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 1.06 MB
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  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Citation Authors

https://github.com/guadag12/scraping-google-scholar/blob/main/ 

## Survival Strategies: Exploring Ministerial Replacement Across Regime Types


Welcome to the repository for my final paper in **GVPT888A**, where I investigate about the intricate dynamics of **ministerial replacement** across different regime types. This project uses Google Scholar to explore the most influential works on ministerial turnover, helping to better understand how regime performance shapes ministerial duration and durability.

This repository contains all the code you need to replicate the work and dive into the literature surrounding ministerial replacement. Here's how you can get started:

1. **Scrape the most cited works on Ministerial Replacement**  
   Run `R code/01_scraping_google_scholar.R` to extract relevant articles from Google Scholar.
   
2. **Extract citation data**  
   Use `Python code/2_get_citations_from_articles.ipynb` to gather citation information from the articles.

3. **Join the data for analysis**  
   Execute `R code/3_join_data.R` to combine the datasets into a unified format.

4. **Visualize the network**  
   Finally, run `R code/4_network.R` to generate visualizations and network analyses based on the gathered data.

You can explore all the output figures and insights from this literature review in the **plots** folder. These figures will help visualize the interconnections between key works and the evolution of thought around ministerial replacement.

Owner

  • Name: Guadalupe Gonzalez
  • Login: guadag12
  • Kind: user
  • Location: Ciudad de Buenos Aires, Argentina
  • Company: Observatorio de Redes

Political scientist trying to surf into data science🔬🏄‍♀️

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