Prada, Gustavo ACantu-Ortiz, Francisco JRodríguez-Acevez, Lucía AlejandraCeballos Cansino, Héctor Gibrán2020-03-142020-03-142013-10-28978-145032414-410.1145/2508497.2508499http://hdl.handle.net/11285/636187For 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.engEmbargoed Accesshttp://creativecommons.org/licenses/by-nc-nd/4.0/ScienceArtículo de conferenciaCompSci 2013 - Proceedings of the 2013 Workshop on Computational Scientometrics: Theory and Applications, Co-located with CIKM 2013Coauthorship networksNetwork visualizationPotential collaboration indexScientific collaborationSocial network analysis712