andrearoota/bachelorThesis

A comprehensive software solution designed to gather, analyze, and visualize bibliometric factors of scientific paper authors.

Bibliometric Factors Analysis for Scientific Paper Authors (bachelor thesis)

A comprehensive software solution designed to gather, analyze, and visualize bibliometric factors of scientific paper authors.

Overview

This project is a culmination of a bachelor's thesis, aiming to provide a holistic tool for bibliometric data collection, analysis, and visualization. It leverages the Scopus API for data acquisition and offers a client-server architecture for data processing and presentation.

Features

• Data Collection: Utilizes the Scopus API to fetch bibliometric data. The scopusBulkDownloader module facilitates this process.
• Backend Analysis: The backend, written in Python, employs Flask for web infrastructure. It offers various analyses, including:
  • Average Coauthors Variation After Years
  • Coauthors Impact on Citations and H-index
  • H-index Influential Articles Timing Analysis
  • And more...
• Frontend Visualization: The frontend is crafted using TypeScript and React, providing a user-friendly interface for data visualization. The main entry point for the frontend can be found here.

Technologies Used

• Backend: Flask, Pandas
• Data Collection: Scopus API, Pybliometrics
• Frontend: TypeScript, React
• Data Processing: Spark, Pandas
• Database: MongoDB
• Containerization: Docker

Setup & Installation

1. Clone the repository.
2. Set up Docker and ensure all dependencies are installed.
3. Follow individual setup instructions for backend and frontend.
4. Run the application using Docker.

License

This project is licensed under the MIT License.