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

@article{Latapy2006BasicNF, title={Basic Notions for the Analysis of Large Affiliation Networks / Bipartite Graphs}, author={Matthieu Latapy and Cl{\'e}mence Magnien and Nathalie Del Vecchio Liafa - Cnrs and 7 UniversiteParis and Crea - Cnrs and Ecole Nationale Polytechnique and 2 LARGEPA-UniversiteParis}, journal={arXiv: Statistical Mechanics}, year={2006} }

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… Expand

#### Figures and Tables from this paper

#### 23 Citations

Theoretical Computer Science special issue on Complex Networks

Complex networks are large networks encountered in practice that seem to lack any apparent structure. Typical complex networks include internet topologies, web graphs, peer-to-peer networks, social… Expand

Clustering coefficient and community structure of bipartite networks

- Mathematics, Physics
- 2008

Many real-world networks display natural bipartite structure, where the basic cycle is a square. In this paper, with the similar consideration of standard clustering coefficient in binary networks, a… Expand

Comparative Definition of Community in Bipartite Network

- Mathematics
- 2009

In order to know the community structure in bipartite network,we propose a comparative definition of community in bipartite network,overlapping between communities is allowed in this definition.We… Expand

Modeling online social networks using Quasi-clique communities

- Computer Science
- 2011

A random graph model that generates social networks using a community-based approach, in which users’ affiliations to communities are explicitly modeled and then translated into a social network, is proposed, which is the first community- based model that can accurately reproduce a variety of important social network characteristics. Expand

Social network of the competing crowd

- Computer Science
- 2014 International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC2014)
- 2014

This paper analyzes the social network among competition participants at Kaggle.com, finding a large number of connected components in these networks, which shows that players at this marketplace are densely but not widely connected. Expand

The structure analysis of user behaviors for web traffic

- Computer Science
- 2009 ISECS International Colloquium on Computing, Communication, Control, and Management
- 2009

The algorithm of finding the community structure in bipartite network divided the clients into different interest communities and obtained the result that the out-degree distribution of clients, the in- degree distribution of servers and the strength distribution is power-law. Expand

The community Analysis of User Behaviors Network for Web Traffic

- Computer Science
- J. Softw.
- 2011

The structure analysis of UBNWT is very helpful for the network management, resource allocation, traffic engineering andSecurity, and the loyalty of clients belonging to the same community in different time is higher than 80%. Expand

An Alternative Approach to the Calculation and Analysis of Connectivity in the World City Network

- Sociology, Physics
- ArXiv
- 2012

An approach in which network centrality measures are interpreted against a randomized baseline model that retains the network's original degree distribution is introduced, which is applied to Taylor's specification of world cities being ‘interlocked’ through the office networks of globalized service firms. Expand

Piecewise-Linear Distance-Dependent Random Graph Models

- 2011

In this paper, we propose a form of random graph (network) model in which the probability of an edge (link) is dependent on a real-valued function on pairs of vertices (nodes). In general, we expect… Expand

Analysing the Use of Ontologies Based on Usage Network

- Computer Science
- 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology
- 2012

To analyse the usage of ontologies by data publishers, the Ontology Usage Network is model, which is a bipartite affiliation network, is used to study statistical and structural properties such as degree distribution, centrality measures and identification of cohesive subgroups. Expand

#### References

SHOWING 1-10 OF 101 REFERENCES

Bipartite structure of all complex networks

- Mathematics, Computer Science
- Inf. Process. Lett.
- 2004

This work proposes the first simple and intuitive model for complex networks which captures the main properties met in practice, and shows here that all complex networks can be viewed as bipartite structures sharing some important statistics, like degree distributions. Expand

Bipartite graphs as models of complex networks

- Physics, Mathematics
- 2006

It appeared recently that the classical random graph model used to represent real-world complex networks does not capture their main properties. Since then, various attempts have been made to provide… Expand

Analysis of weighted networks.

- Mathematics, Physics
- Physical review. E, Statistical, nonlinear, and soft matter physics
- 2004

It is pointed out that weighted networks can in many cases be analyzed using a simple mapping from a weighted network to an unweighted multigraph, allowing us to apply standard techniques for unweighting graphs to weighted ones as well. Expand

The architecture of complex weighted networks.

- Mathematics, Physics
- Proceedings of the National Academy of Sciences of the United States of America
- 2004

This work studies the scientific collaboration network and the world-wide air-transportation network, which are representative examples of social and large infrastructure systems, respectively, and defines appropriate metrics combining weighted and topological observables that enable it to characterize the complex statistical properties and heterogeneity of the actual strength of edges and vertices. Expand

Random graph models of social networks

- Computer Science, Medicine
- Proceedings of the National Academy of Sciences of the United States of America
- 2002

It is found that in some cases, the models are in remarkable agreement with the data, whereas in others the agreement is poorer, perhaps indicating the presence of additional social structure in the network that is not captured by the random graph. Expand

Cycles and clustering in bipartite networks.

- Mathematics, Medicine
- Physical review. E, Statistical, nonlinear, and soft matter physics
- 2005

An expression is deduced for estimating cycles of larger size, which improves previous estimations and is suitable for either monopartite and multipartite networks, and the applicability of such analytical estimations is discussed. Expand

Characterization and modeling of weighted networks

- Computer Science, Physics
- 2005

The main empirical results are the broad distributions of various quantities and the existence of weight-topology correlations which show that weights are relevant and that in general the modeling of complex networks must go beyond topology. Expand

Correlations in bipartite collaboration networks

- Mathematics, Physics
- 2006

Collaboration networks are studied as an example of growing bipartite networks. These have been previously observed to exhibit structure such as positive correlations between nearest-neighbour… Expand

Random graphs with arbitrary degree distributions and their applications.

- Mathematics, Physics
- Physical review. E, Statistical, nonlinear, and soft matter physics
- 2001

It is demonstrated that in some cases random graphs with appropriate distributions of vertex degree predict with surprising accuracy the behavior of the real world, while in others there is a measurable discrepancy between theory and reality, perhaps indicating the presence of additional social structure in the network that is not captured by the random graph. Expand

Handbook of Graphs and Networks: From the Genome to the Internet

- Computer Science
- 2003

This book defines the field of complex interacting networks in its infancy and presents the dynamics of networks and their structure as a key concept across disciplines and offers concepts to model network structures and dynamics, focussed on approaches applicable across disciplines. Expand