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Visualizing Co-Authorship Social Networks and Collaboration Recommendations With CNARe

Visualizing Co-Authorship Social Networks and Collaboration Recommendations With CNARe

Michele A. Brandão, Matheus A. Diniz, Guilherme A. de Sousa, Mirella M. Moro
Copyright: © 2018 |Pages: 16
ISBN13: 9781522528142|ISBN10: 1522528148|EISBN13: 9781522528159
DOI: 10.4018/978-1-5225-2814-2.ch011
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MLA

Brandão, Michele A., et al. "Visualizing Co-Authorship Social Networks and Collaboration Recommendations With CNARe." Graph Theoretic Approaches for Analyzing Large-Scale Social Networks, edited by Natarajan Meghanathan, IGI Global, 2018, pp. 173-188. https://doi.org/10.4018/978-1-5225-2814-2.ch011

APA

Brandão, M. A., Diniz, M. A., de Sousa, G. A., & Moro, M. M. (2018). Visualizing Co-Authorship Social Networks and Collaboration Recommendations With CNARe. In N. Meghanathan (Ed.), Graph Theoretic Approaches for Analyzing Large-Scale Social Networks (pp. 173-188). IGI Global. https://doi.org/10.4018/978-1-5225-2814-2.ch011

Chicago

Brandão, Michele A., et al. "Visualizing Co-Authorship Social Networks and Collaboration Recommendations With CNARe." In Graph Theoretic Approaches for Analyzing Large-Scale Social Networks, edited by Natarajan Meghanathan, 173-188. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-2814-2.ch011

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Abstract

Studies have analyzed social networks considering a plethora of metrics for different goals, from improving e-learning to recommend people and things. Here, we focus on large-scale social networks defined by researchers and their common published articles, which form co-authorship social networks. Then, we introduce CNARe, an online tool that analyzes the networks and present recommendations of collaborations based on three different algorithms (Affin, CORALS and MVCWalker). Through visualizations and social networks metrics, CNARe also allows to investigate how the recommendations affect the co-authorship social networks, how researchers' networks are in a central and eagle-eye context, and how the strength of ties behaves in large co-authorship social networks. Furthermore, users can upload their own network in CNARe and make their own recommendation and social network analysis.

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