Basic Notions for the Analysis of Large Affiliation Networks / Bipartite Graphs

Abstract

Many real-world complex networks actually have a bipartite nature: their nodes may be separated into two classes, the links being between nodes of different classes only. Despite this, and despite the fact that many ad-hoc tools have been designed for the study of special cases, very few exist to analyse (describe, extract relevant information) such networks in a systematic way. We propose here an extension of the most basic notions used nowadays to analyse classical complex networks to the bipartite case. To achieve this, we introduce a set of simple statistics, which we discuss by comparing their values on a representative set of real-world networks and on their random versions.

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• Statistical mechanics of complex networks
• The structure and function of complex networks
• The architecture of complex weighted networks
• Random graphs with arbitrary degree distributions and their applications
• Mixing patterns in networks
• Who is the best connected scientist? A study of scientific coauthorship networks
• Analysis of weighted networks
• Characterization and Modeling of weighted networks
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• Human Sexual Contact Network as a Bipartite Graph
• Bipartite Producer-Consumer Networks and the Size Distribution of Firms
• Construction of bipartite and unipartite weighted networks from collections of journal papers
• A Connection-Centric Survey of Recommender Systems Research

Cited by in corpus (5)

• The clustering coefficient and community structure of bipartite networks
• An Alternative Approach to the Calculation and Analysis of Connectivity in the World City Network
• Clash of the Trackers: Measuring the Evolution of the Online Tracking Ecosystem
• sGrapp: Butterfly Approximation in Streaming Graphs
• Phase transitions in a decentralized graph-based approach to human language