Assessing the influence of bibliometric factors and organizational characteristics on the centrality degree of inter-university collaborative networks: a neural network approach
Introduction. The centrality degree of a university collaborative network indicates how many other universities the given university has active collaborations with. The study analyses the centrality of university-level collaboration networks and aim to assess the influence of organizational characte...
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| Language: | English |
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University of Borås
2024-03-01
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| Series: | Information Research: An International Electronic Journal |
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| Online Access: | https://informationr.net/infres/article/view/427 |
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| author | Juan David Reyes-Gómez Efrén Romero-Riaño |
| author_facet | Juan David Reyes-Gómez Efrén Romero-Riaño |
| author_sort | Juan David Reyes-Gómez |
| collection | DOAJ |
| description | Introduction. The centrality degree of a university collaborative network indicates how many other universities the given university has active collaborations with. The study analyses the centrality of university-level collaboration networks and aim to assess the influence of organizational characteristics and bibliometric factors of universities on the centrality degree.
Method. This study used artificial neural networks, particularly a multilayer perceptron. The input variables included number of documents published, citations, size, type, and location of the university. Data was extracted from the census of institutions identified within the inter-university collaborative networks of Santander and Caldas in Colombia. A total of 154 universities comprises the dataset for the territory of Santander and 126 for Caldas.
Results. The results indicated that bibliometric factors had a significant influence on the centrality degree of the networks. Organizational characteristics also had an influence, but to a lesser extent than bibliometric factors.
Conclusion. The study found that the research output and impact are the most important factors in predicting the centrality degree of a university in a collaborative network. This suggests that policies to increase the research output and impact of a university are likely to result in a more central position in the network. |
| format | Article |
| id | doaj-art-f621efdc0cc44bac9b2cb40916244183 |
| institution | Kabale University |
| issn | 1368-1613 |
| language | English |
| publishDate | 2024-03-01 |
| publisher | University of Borås |
| record_format | Article |
| series | Information Research: An International Electronic Journal |
| spelling | doaj-art-f621efdc0cc44bac9b2cb409162441832025-02-03T10:10:34ZengUniversity of BoråsInformation Research: An International Electronic Journal1368-16132024-03-01291203310.47989/ir291427424Assessing the influence of bibliometric factors and organizational characteristics on the centrality degree of inter-university collaborative networks: a neural network approachJuan David Reyes-Gómez0https://orcid.org/0000-0001-5093-8097Efrén Romero-Riaño1https://orcid.org/0000-0002-3627-9942Universidad Colegio Mayor de CundinamarcaColombian Observatory of Science and Technology - OCyTIntroduction. The centrality degree of a university collaborative network indicates how many other universities the given university has active collaborations with. The study analyses the centrality of university-level collaboration networks and aim to assess the influence of organizational characteristics and bibliometric factors of universities on the centrality degree. Method. This study used artificial neural networks, particularly a multilayer perceptron. The input variables included number of documents published, citations, size, type, and location of the university. Data was extracted from the census of institutions identified within the inter-university collaborative networks of Santander and Caldas in Colombia. A total of 154 universities comprises the dataset for the territory of Santander and 126 for Caldas. Results. The results indicated that bibliometric factors had a significant influence on the centrality degree of the networks. Organizational characteristics also had an influence, but to a lesser extent than bibliometric factors. Conclusion. The study found that the research output and impact are the most important factors in predicting the centrality degree of a university in a collaborative network. This suggests that policies to increase the research output and impact of a university are likely to result in a more central position in the network.https://informationr.net/infres/article/view/427inter-university collaborative networksbibliometric factorsorganizational characteristicscentrality degreeneural network |
| spellingShingle | Juan David Reyes-Gómez Efrén Romero-Riaño Assessing the influence of bibliometric factors and organizational characteristics on the centrality degree of inter-university collaborative networks: a neural network approach Information Research: An International Electronic Journal inter-university collaborative networks bibliometric factors organizational characteristics centrality degree neural network |
| title | Assessing the influence of bibliometric factors and organizational characteristics on the centrality degree of inter-university collaborative networks: a neural network approach |
| title_full | Assessing the influence of bibliometric factors and organizational characteristics on the centrality degree of inter-university collaborative networks: a neural network approach |
| title_fullStr | Assessing the influence of bibliometric factors and organizational characteristics on the centrality degree of inter-university collaborative networks: a neural network approach |
| title_full_unstemmed | Assessing the influence of bibliometric factors and organizational characteristics on the centrality degree of inter-university collaborative networks: a neural network approach |
| title_short | Assessing the influence of bibliometric factors and organizational characteristics on the centrality degree of inter-university collaborative networks: a neural network approach |
| title_sort | assessing the influence of bibliometric factors and organizational characteristics on the centrality degree of inter university collaborative networks a neural network approach |
| topic | inter-university collaborative networks bibliometric factors organizational characteristics centrality degree neural network |
| url | https://informationr.net/infres/article/view/427 |
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