SNAP: A General Purpose Network Analysis and Graph Mining Library
Jure Leskovec, Rok Sosic

TL;DR
SNAP is a high-performance, open-source library designed for efficient analysis and manipulation of large, dynamic networks, supporting a wide range of algorithms and datasets for research across disciplines.
Contribution
The paper introduces SNAP, a versatile, optimized system for large-scale network analysis, with extensive algorithm support and dynamic graph handling capabilities.
Findings
SNAP can process networks with hundreds of millions of nodes and billions of edges.
It offers over 140 graph algorithms for various analysis tasks.
SNAP's performance benchmarks demonstrate high efficiency on large datasets.
Abstract
Large networks are becoming a widely used abstraction for studying complex systems in a broad set of disciplines, ranging from social network analysis to molecular biology and neuroscience. Despite an increasing need to analyze and manipulate large networks, only a limited number of tools are available for this task. Here, we describe Stanford Network Analysis Platform (SNAP), a general-purpose, high-performance system that provides easy to use, high-level operations for analysis and manipulation of large networks. We present SNAP functionality, describe its implementational details, and give performance benchmarks. SNAP has been developed for single big-memory machines and it balances the trade-off between maximum performance, compact in-memory graph representation, and the ability to handle dynamic graphs where nodes and edges are being added or removed over time. SNAP can process…
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Taxonomy
TopicsComplex Network Analysis Techniques · Advanced Graph Neural Networks · Bioinformatics and Genomic Networks
