Structure constrained by metadata in networks of chess players
Fil: Almeira, Nahuel. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina.
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | info:eu-repo/semantics/publishedVersion |
| Language: | eng |
| Published: |
2024
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| Subjects: | |
| Online Access: | http://hdl.handle.net/11086/551568 https://doi.org/10.1038/s41598-017-15428-z |
| _version_ | 1801214063955410944 |
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| author | Almeira, Nahuel Schaigorodsky, Ana Laura Perotti, Juan Ignacio Billoni, Orlando Vito |
| author2 | https://orcid.org/0000-0002-0207-4025 |
| author_facet | https://orcid.org/0000-0002-0207-4025 Almeira, Nahuel Schaigorodsky, Ana Laura Perotti, Juan Ignacio Billoni, Orlando Vito |
| author_sort | Almeira, Nahuel |
| collection | Repositorio Digital Universitario |
| description | Fil: Almeira, Nahuel. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. |
| format | info:eu-repo/semantics/publishedVersion |
| id | rdu-unc.551568 |
| institution | Universidad Nacional de Cordoba |
| language | eng |
| publishDate | 2024 |
| record_format | dspace |
| spelling | rdu-unc.5515682024-04-25T06:36:30Z Structure constrained by metadata in networks of chess players Almeira, Nahuel Schaigorodsky, Ana Laura Perotti, Juan Ignacio Billoni, Orlando Vito https://orcid.org/0000-0002-0207-4025 https://orcid.org/0000-0001-7424-9552 https://orcid.org/0000-0001-9452-4400 Complex networks Statistical physics Redes complejas Detección de comunidades info:eu-repo/semantics/publishedVersion Fil: Almeira, Nahuel. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Almeira, Nahuel. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina. Fil: Almeira, Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física Enrique Gaviola; Argentina. Fil: Schaigorodsky, Ana Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Schaigorodsky, Ana Laura. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina. Fil: Schaigorodsky, Ana Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física Enrique Gaviola; Argentina. Fil: Perotti, Juan Ignacio. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Perotti, Juan Ignacio. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina. Fil: Perotti, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física Enrique Gaviola; Argentina. Fil: Billoni, Orlando Vito. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Billoni, Orlando Vito. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina. Fil: Billoni, Orlando Vito. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física Enrique Gaviola; Argentina. Chess is an emblematic sport that stands out because of its age, popularity and complexity. It has served to study human behavior from the perspective of a wide number of disciplines, from cognitive skills such as memory and learning, to aspects like innovation and decision-making. Given that an extensive documentation of chess games played throughout history is available, it is possible to perform detailed and statistically significant studies about this sport. Here we use one of the most extensive chess databases in the world to construct two networks of chess players. One of the networks includes games that were played over-the-board and the other contains games played on the Internet. We study the main topological characteristics of the networks, such as degree distribution and correlations, transitivity and community structure. We complement the structural analysis by incorporating players’ level of play as node metadata. Although both networks are topologically different, we show that in both cases players gather in communities according to their expertise and that an emergent rich-club structure, composed by the top-rated players, is also present. info:eu-repo/semantics/publishedVersion Fil: Almeira, Nahuel. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Almeira, Nahuel. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina. Fil: Almeira, Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física Enrique Gaviola; Argentina. Fil: Schaigorodsky, Ana Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Schaigorodsky, Ana Laura. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina. Fil: Schaigorodsky, Ana Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física Enrique Gaviola; Argentina. Fil: Perotti, Juan Ignacio. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Perotti, Juan Ignacio. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina. Fil: Perotti, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física Enrique Gaviola; Argentina. Fil: Billoni, Orlando Vito. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Billoni, Orlando Vito. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina. Fil: Billoni, Orlando Vito. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física Enrique Gaviola; Argentina. Otras Ciencias Físicas 2024-04-24T14:10:03Z 2024-04-24T14:10:03Z 2017 article Almeira, N., Schaigorodsky, A. L., Perotti, J. I. y Billoni, O. V. (2017). Structure constrained by metadata in networks of chess players. Scientific Reports, 7, 15186. https://doi.org/10.1038/s41598-017-15428-z http://hdl.handle.net/11086/551568 https://doi.org/10.1038/s41598-017-15428-z eng Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ e-ISSN: 2045-2322 |
| spellingShingle | Complex networks Statistical physics Redes complejas Detección de comunidades Almeira, Nahuel Schaigorodsky, Ana Laura Perotti, Juan Ignacio Billoni, Orlando Vito Structure constrained by metadata in networks of chess players |
| title | Structure constrained by metadata in networks of chess players |
| title_full | Structure constrained by metadata in networks of chess players |
| title_fullStr | Structure constrained by metadata in networks of chess players |
| title_full_unstemmed | Structure constrained by metadata in networks of chess players |
| title_short | Structure constrained by metadata in networks of chess players |
| title_sort | structure constrained by metadata in networks of chess players |
| topic | Complex networks Statistical physics Redes complejas Detección de comunidades |
| url | http://hdl.handle.net/11086/551568 https://doi.org/10.1038/s41598-017-15428-z |
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