A growth model for citations networks
Abstract In some complex networks, nodes can continuously increase or decrease the number of their incoming and outgoing links. The World Wide Web is one such example, as webmasters can add or delete hyperlinks on web pages at any time. There are also networks where this can not happen. For instance...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-01-01
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| Series: | Applied Network Science |
| Online Access: | https://doi.org/10.1007/s41109-025-00691-1 |
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| _version_ | 1832594940403646464 |
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| author | Pedro Castillo-Castillo Enrique Stevens-Navarro Ulises Pineda-Rico Abel Garcia-Barrientos Francisco R. Castillo-Soria Jesus Acosta-Elias |
| author_facet | Pedro Castillo-Castillo Enrique Stevens-Navarro Ulises Pineda-Rico Abel Garcia-Barrientos Francisco R. Castillo-Soria Jesus Acosta-Elias |
| author_sort | Pedro Castillo-Castillo |
| collection | DOAJ |
| description | Abstract In some complex networks, nodes can continuously increase or decrease the number of their incoming and outgoing links. The World Wide Web is one such example, as webmasters can add or delete hyperlinks on web pages at any time. There are also networks where this can not happen. For instance, in citation networks of scientific articles, after an article has been published, it will start gaining incoming links as it is cited, but its outgoing links will remain unchanged. Although articles are published with a predetermined number of references, the distribution of their outgoing links follows a power law, as if they were the result of a preferential process. So, how can we explain that the number of references an author includes in a scientific article is not purely random? In this work, a growth model for citation networks is presented, proposing that the distribution of outgoing links can be shaped by the presence of communities. |
| format | Article |
| id | doaj-art-e2db634de39d4050b38b0ff0d00de4b9 |
| institution | Kabale University |
| issn | 2364-8228 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Applied Network Science |
| spelling | doaj-art-e2db634de39d4050b38b0ff0d00de4b92025-01-19T12:14:01ZengSpringerOpenApplied Network Science2364-82282025-01-011011810.1007/s41109-025-00691-1A growth model for citations networksPedro Castillo-Castillo0Enrique Stevens-Navarro1Ulises Pineda-Rico2Abel Garcia-Barrientos3Francisco R. Castillo-Soria4Jesus Acosta-Elias5Facultad de Ciencias, Universidad Autonoma de San Luis PotosiFacultad de Ciencias, Universidad Autonoma de San Luis PotosiFacultad de Ciencias, Universidad Autonoma de San Luis PotosiFacultad de Ciencias, Universidad Autonoma de San Luis PotosiFacultad de Ciencias, Universidad Autonoma de San Luis PotosiFacultad de Ciencias, Universidad Autonoma de San Luis PotosiAbstract In some complex networks, nodes can continuously increase or decrease the number of their incoming and outgoing links. The World Wide Web is one such example, as webmasters can add or delete hyperlinks on web pages at any time. There are also networks where this can not happen. For instance, in citation networks of scientific articles, after an article has been published, it will start gaining incoming links as it is cited, but its outgoing links will remain unchanged. Although articles are published with a predetermined number of references, the distribution of their outgoing links follows a power law, as if they were the result of a preferential process. So, how can we explain that the number of references an author includes in a scientific article is not purely random? In this work, a growth model for citation networks is presented, proposing that the distribution of outgoing links can be shaped by the presence of communities.https://doi.org/10.1007/s41109-025-00691-1 |
| spellingShingle | Pedro Castillo-Castillo Enrique Stevens-Navarro Ulises Pineda-Rico Abel Garcia-Barrientos Francisco R. Castillo-Soria Jesus Acosta-Elias A growth model for citations networks Applied Network Science |
| title | A growth model for citations networks |
| title_full | A growth model for citations networks |
| title_fullStr | A growth model for citations networks |
| title_full_unstemmed | A growth model for citations networks |
| title_short | A growth model for citations networks |
| title_sort | growth model for citations networks |
| url | https://doi.org/10.1007/s41109-025-00691-1 |
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