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Recommending intra-institutional scientific collaboration through coauthorship network visualization
| Content Provider | ACM Digital Library |
|---|---|
| Author | Ceballos, Hector G. Cantu, Francisco J. Rodriguez-Aceves, Lucia Parada, Gustavo A. |
| Abstract | For improving research productivity, quality and dissemination, we propose the development of a visual recommendation tool summing up scientific collaboration best-practices found in literature. Social Network Analysis are applied to a coauthorship network for generating a Potential Collaboration Index (PCI) based on productivity, connectivity, similarity and expertise. This work is evaluated by recommending intra-institutional collaboration in a comprehensive university. The accuracy of PCI is documented, along with suggestions and comments from 27 interviewed researchers. |
| Starting Page | 7 |
| Ending Page | 12 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781450324144 |
| DOI | 10.1145/2508497.2508499 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-10-28 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Scientific collaboration Social network analysis Potential collaboration index Network visualization Coauthorship networks |
| Content Type | Text |
| Resource Type | Article |
