6533b85ffe1ef96bd12c1db9
RESEARCH PRODUCT
Core of communities in bipartite networks
Christian BongiornoAndrás LondonRosario N. MantegnaRosario N. MantegnaRosario N. MantegnaSalvatore Miccichèsubject
FOS: Computer and information sciencesAccuracy and precisionPhysics - Physics and SocietyBipartite systemRand indexFOS: Physical sciencesPhysics and Society (physics.soc-ph)computer.software_genre01 natural sciences010104 statistics & probabilityRobustness (computer science)0103 physical sciences01.02. Számítás- és információtudomány0101 mathematics010306 general physicsMathematicsSocial and Information Networks (cs.SI)Probability and statisticsComputer Science - Social and Information NetworksSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)network theory community detectionPhysics - Data Analysis Statistics and ProbabilityBipartite graphData miningcomputerData Analysis Statistics and Probability (physics.data-an)description
We use the information present in a bipartite network to detect cores of communities of each set of the bipartite system. Cores of communities are found by investigating statistically validated projected networks obtained using information present in the bipartite network. Cores of communities are highly informative and robust with respect to the presence of errors or missing entries in the bipartite network. We assess the statistical robustness of cores by investigating an artificial benchmark network, the co-authorship network, and the actor-movie network. The accuracy and precision of the partition obtained with respect to the reference partition are measured in terms of the adjusted Rand index and of the adjusted Wallace index respectively. The detection of cores is highly precise although the accuracy of the methodology can be limited in some cases.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2017-03-06 |