network

Chapter 3 Network Data and Analysis Tools

Table of Contents

Obsidian Vault Personal Branding, Research & Learning Network theory, Knowledge Graphs and GNNs Chapter 3 Network Data and Analysis Tools   Network data sources Reza Rezazadegan The data for yours data analysis project can be taken from the following sources and the analysis can be related to your presentation topic.

Stanford Large Network Dataset Collection

http://snap.stanford.edu/data/index.html http://snap.stanford.edu/data/other.html

Network Repository

https://networkrepository.com/index.php

UC Irvine Network Repository

https://networkdata.ics.uci.edu/

Social and Communication Networks from Yahoo!

https://webscope.sandbox.yahoo.com/catalog.php?datatype=g

Netzschleuder

https://networks.skewed.de/

Konect

http://konect.cc/networks/

Others

http://math.bu.edu/people/kolaczyk/datasets.html https://public.websites.umich.edu/~mejn/netdata/

Network Visualization and Analysis Software

Gephi

Cytoscape

UCINET

for whole-network analysis

Pajek

Python Libraries

iGraph

  • Written in C, available for both R and Python
  • Suitable for huge networks with nodes
  • Good network visualization tools
  • Doesn’t have a very handy API

SNAP.py

https://snap.stanford.edu/snappy/

Networkx

Convenient for networks up to 100000 nodes.

Introduction to Networkx

Installing Python

Install Miniconda from https://docs.anaconda.com/free/miniconda/miniconda-install.html Then open the Anaconda Prompt and enter pip install networkx jupyter pandas matplotlibCopy Get Visual Studio Code from https://code.visualstudio.com/download Install the Jupyter plugin in VSCode. Optionally install the AI plugin Amazon Code Whisperer.

Networkx tutorial

We use this jupyter notebook: https://networkx.org/documentation/stable/tutorial.ipynb Full Networkx reference: https://networkx.org/documentation/hstable/reference/index.html

Student presentations from the book Complex Network Analysis with Python

Students make groups of two to present the following chapters:

Chapter 3: Constructing a network of Wikipedia pages

Chapter 9: Panama Papers

Chapter 13: Going from Products to Projects

Chapter 16: Building a network of trauma types

Graph Visualization Layouts

Because the networks we study are abstract, there are different ways to draw each network. Topic for a small student presentation!    

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