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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2022
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2208.06431 |
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| _version_ | 1866908341141241856 |
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| author | Baccini, Federica Barabesi, Lucio Petrovich, Eugenio |
| author_facet | Baccini, Federica Barabesi, Lucio Petrovich, Eugenio |
| contents | We introduce a methodology based on averaging similarity matrices with the aim of integrating the layers of a multiplex network into a single monoplex network. Multiplex networks are adopted for modelling a wide variety of real-world frameworks, such as multi-type relations in social, economic and biological structures. More specifically, multiplex networks are used when relations of different nature (layers) arise between a set of elements from a given population (nodes). A possible approach for investigating multiplex networks consists in aggregating the different layers in a single network (monoplex) which is a valid representation -- in some sense -- of all the layers. In order to obtain such an aggregated network, we propose a theoretical approach -- along with its practical implementation -- which stems on the concept of similarity matrix average. This methodology is finally applied to a multiplex similarity network of statistical journals, where the three considered layers express the similarity of the journals based on co-citations, common authors and common editors, respectively. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2208_06431 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Similarity matrix average for aggregating multiplex networks Baccini, Federica Barabesi, Lucio Petrovich, Eugenio Physics and Society Computational Geometry Data Analysis, Statistics and Probability Methodology 68U01 G.3; I.0; J.2 We introduce a methodology based on averaging similarity matrices with the aim of integrating the layers of a multiplex network into a single monoplex network. Multiplex networks are adopted for modelling a wide variety of real-world frameworks, such as multi-type relations in social, economic and biological structures. More specifically, multiplex networks are used when relations of different nature (layers) arise between a set of elements from a given population (nodes). A possible approach for investigating multiplex networks consists in aggregating the different layers in a single network (monoplex) which is a valid representation -- in some sense -- of all the layers. In order to obtain such an aggregated network, we propose a theoretical approach -- along with its practical implementation -- which stems on the concept of similarity matrix average. This methodology is finally applied to a multiplex similarity network of statistical journals, where the three considered layers express the similarity of the journals based on co-citations, common authors and common editors, respectively. |
| title | Similarity matrix average for aggregating multiplex networks |
| topic | Physics and Society Computational Geometry Data Analysis, Statistics and Probability Methodology 68U01 G.3; I.0; J.2 |
| url | https://arxiv.org/abs/2208.06431 |