### Résumé

Many real-world complex networks are best modeled as bipartite (or 2-mode) graphs, where nodes are divided into two sets with links connecting one side to the other. However, there is currently a lack of methods to analyze properly such graphs as most existing measures and methods are suited to classical graphs. A usual but limited approach consists in deriving 1-mode graphs (called projections) from the underlying bipartite structure, though it causes important loss of information and data storage issues. We introduce here internal links and pairs as a new notion useful for such analysis: it gives insights on the information lost by projecting the bipartite graph. We illustrate the relevance of theses concepts on several real-world instances illustrating how it enables to discriminate behaviors among various cases when we compare them to a benchmark of random networks. Then, we show that we can draw benefit from this concept for both modeling complex networks and storing them in a compact format.

langue originale | Anglais |
---|---|

journal | Social Network Analysis and Mining |

Etat de la publication | Publié - 22 avr. 2011 |

## Empreinte digitale Examiner les sujets de recherche de « Internal links and pairs as a new tool for the analysis of bipartite complex networks ». Ensemble, ils forment une empreinte digitale unique.

## Contient cette citation

Allali, O., Tabourier, L., Magnien, C., & Latapy, M. (2011). Internal links and pairs as a new tool for the analysis of bipartite complex networks.

*Social Network Analysis and Mining*.