SNAP – Stanford Network Analysis Platform

About SNAP
The SNAP library is being actively developed since 2004 and is organically growing as a result of our research pursuits in analysis of large social and information networks. Largest network we analyzed so far using the library was the Microsoft Instant Messenger network from 2006 with 240 million nodes and 1.3 billion edges.
The datasets available on the website were mostly collected (scraped) for the purposes of our research.
The website was launched in July 2009.
Source: http://snap.stanford.edu/about.html

SNAP for C++: Stanford Network Analysis Platform
Stanford Network Analysis Platform (SNAP) is a general purpose network analysis and graph mining library. It is written in C++ and easily scales to massive networks with hundreds of millions of nodes, and billions of edges. It efficiently manipulates large graphs, calculates structural properties, generates regular and random graphs, and supports attributes on nodes and edges. SNAP is also available through the NodeXL which is a graphical front-end that integrates network analysis into Microsoft Office and Excel.
Stanford Network Analysis Platform (SNAP) is a general purpose, high performance system for analysis and manipulation of large networks. Graphs consists of nodes and directed/undirected/multiple edges between the graph nodes. Networks are graphs with data on nodes and/or edges of the network.
The core SNAP library is written in C++ and optimized for maximum performance and compact graph representation. It easily scales to massive networks with hundreds of millions of nodes, and billions of edges. It efficiently manipulates large graphs, calculates structural properties, generates regular and random graphs, and supports attributes on nodes and edges. Besides scalability to large graphs, an additional strength of SNAP is that nodes, edges and attributes in a graph or a network can be changed dynamically during the computation.
SNAP was originally developed by Jure Leskovec in the course of his PhD studies. The first release was made available in Nov, 2009. SNAP uses a general purpose STL (Standard Template Library)-like library GLib developed at Jozef Stefan Institute. SNAP and GLib are being actively developed and used in numerous academic and industrial projects.
Source: http://snap.stanford.edu/snap/index.html

Snap.py: SNAP for Python
Snap.py is a Python interface for SNAP. It provides performance benefits of SNAP, combined with flexibility of Python. Most of the SNAP C++ functionality is available via Snap.py in Python.
SNAP is a general purpose, high performance system for analysis and manipulation of large networks. SNAP is written in C++ and optimized for maximum performance and compact graph representation. It easily scales to massive networks with hundreds of millions of nodes, and billions of edges.
Snap.py provides performance benefits of SNAP, combined with flexibility of Python. Most of the SNAP functionality is available via Snap.py in Python.
The latest version of Snap.py is 5.0 (Sep 10, 2019), available for macOS, Linux (Ubuntu and CentOS), and Windows 64-bit. Two major new features of this release are support for Python 3.x and pip install.
Source: http://snap.stanford.edu/snappy/index.html

Stanford Large Network Dataset Collection
A collection of more than 50 large network datasets from tens of thousands of nodes and edges to tens of millions of nodes and edges. In includes social networks, web graphs, road networks, internet networks, citation networks, collaboration networks, and communication networks.
Source: http://snap.stanford.edu/data/index.html

Source:
http://memetracker.org/snap/index.html
http://snap.stanford.edu/index.html
http://memetracker.org/snap/doc.html
http://memetracker.org/snap/quick.html
http://memetracker.org/snap/download.html

Interested on library and information science, literacy, digital library, digital humanities, data science, media and culture studies.

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