hevrk

MRC Network Analysis: Uncovering Research Trends in Mathematics

Table of Contents

• Overview
• Getting Started
• Installation
• Usage
• Topics Covered
• Scripts
• Contributing
• License
• Contact

Overview

This repository contains scripts for network analysis of topics discovered by Math Research Compass. The aim is to explore and visualize relationships in mathematical research, leveraging various data science techniques and tools.

For the latest updates and downloads, visit the Releases section.

Getting Started

To get started with this project, you will need to have Python installed on your machine. The scripts utilize libraries such as networkx, bertopic, and others to perform analysis on the arXiv dataset.

Prerequisites

• Python 3.7 or higher
• Libraries: networkx, pandas, numpy, bertopic, matplotlib, seaborn, scikit-learn

You can install the required libraries using pip:

pip install networkx pandas numpy bertopic matplotlib seaborn scikit-learn

Installation

Clone the repository to your local machine:

git clone https://github.com/hevrk/MRC-Network-Analysis.git
cd MRC-Network-Analysis

For specific releases, check the Releases section. Download the necessary files and execute them as instructed.

Usage

After setting up the environment, you can run the scripts to perform various analyses. Each script is designed to address different aspects of network analysis.

Running Scripts

To execute a script, use the following command in your terminal:

python script_name.py

Replace script_name.py with the name of the script you want to run.

Example

For instance, to run the topic modeling script, use:

python topic_modeling.py

This script will analyze the arXiv dataset and produce a network graph of topics.

Topics Covered

This project delves into several topics relevant to mathematical research and network analysis:

• arxiv-dataset: Focus on extracting and analyzing data from the arXiv repository.
• bertopic: Implementation of topic modeling to uncover hidden themes in research papers.
• data-science: Application of data science techniques to analyze and visualize data.
• mathematical-research: Exploration of trends and collaborations in the field of mathematics.
• network-analysis: Techniques to analyze and visualize networks formed by research papers and authors.
• networkx: Use of the NetworkX library for creating and manipulating complex networks.
• research-network: Investigation of how researchers collaborate and influence each other.
• scientific-collaboration: Analysis of co-authorship networks to understand collaborative patterns.
• scientometrics: Study of quantitative aspects of science, including publication and citation analysis.
• topic-modeling: Techniques to identify and categorize topics within a collection of documents.

Scripts

Here is a brief overview of the main scripts available in this repository:

1. data_extraction.py

This script extracts data from the arXiv API and prepares it for analysis.

2. topic_modeling.py

Utilizes the BERTopic library to identify and visualize topics within the dataset.

3. network_visualization.py

Generates visual representations of the research network, showcasing relationships between papers and authors.

4. collaboration_analysis.py

Analyzes co-authorship patterns and generates metrics related to scientific collaboration.

5. scientometrics_analysis.py

Focuses on publication trends, citation counts, and other metrics relevant to scientific output.

6. network_metrics.py

Calculates various network metrics, such as degree centrality and clustering coefficients.

Contributing

Contributions are welcome! If you have suggestions for improvements or new features, please fork the repository and submit a pull request.

Steps to Contribute

1. Fork the repository.
2. Create a new branch for your feature or fix.
3. Make your changes.
4. Commit your changes with a clear message.
5. Push to your branch.
6. Submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For any inquiries or suggestions, please reach out to the repository maintainer:

• Name: [Your Name]
• Email: [Your Email]
• GitHub: [Your GitHub Profile]

For updates and downloads, don’t forget to check the Releases section.