GEAR Network Documentation

The GEAR Network is funded by a $5M grant from the U.S. National Science Foundation’s Research Networks in Mathematical Sciences (RNMS) program.The acronym GEAR stands for GEometric structures And Representation varieties and reflects the mathematical focus of the network (described here). The GEAR Network brings together researchers from over 90 nodes at mathematics centers throughout the world.

Introduction

This documentation serves as a guide on how to use our program to construct network based on publications of GEAR members and generate documents for the GEAR website to visualize the network.

Prerequisite

• Python 2.x
• Packages: BeautifulSoup, pyprind, json
• MathSciNet subscription (e.g. campus internet connection)

Windows:

0. Connect to school wifi
   Useful information: https://answers.uillinois.edu/illinois/page.php?id=47507
   Please choose TunnelAll for "Group"

1. Install Python 2.7
   Download Anaconda https://www.continuum.io/downloads#_windows
   Check "Register Anaconda as my default Python 2.7" in case you have previously installed Python.

2. Download our package
   You can download this code package by https://codeload.github.com/LargePanda/GEAR_Network/zip/master
   A ZIP file will be downloaded and you need to unzip it.

3. Run the program
   Navigate to root of the package, open 'scripts', right click "run", choose "Run as Administrator"
   If there are files with valid contents in /output folder, then it runs successfully

4. Check
   'website_input' folder should have: profile.json, papers.json
   'gephi_input' folder should have co-citation and co-authorship matrices

5. After get output from Gephi
   Navigate to root of the package, open 'scripts', right click "run_after_gephi", choose "Run as Administrator"

6. Get yearly paper list
   Navigate to root of the package, open 'scripts', right click "yearly_papers", choose "Run as Administrator"

Mac:

Open terminal and type the following lines one by one ending with ENTER

    pip install beautifulsoup4
    pip install pyprind

Execution

• Short Version

• Complete Version

ipython notebook version