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Collaboration Networks Analysis: Combining Structural and Keyword-Based Approaches

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Semantic Keyword-Based Search on Structured Data Sources (IKC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10546))

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Abstract

This paper proposes a method for the analysis of the characteristics of collaboration networks. The method uses social network analysis metrics which are especially applicable to directed and weighted collaboration networks. By using the proposed method it is possible to investigate the global structure of the collaboration networks, such as density, centralisation, assortativity and the dynamics of network growth. Furthermore, the method proposes appropriate network centrality measures (degree and its variations for directed and weighted networks) for ranking the nodes. In addition the proposed method combines a keyword-based approach and Louvain algorithm for the community detection task. Next, the paper describes a case study in which the proposed method is applied to the collaboration networks emerged from STSMs on the KEYSTONE COST Action.

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Author information

Authors and Affiliations

  1. Department of Informatics, University of Rijeka, Radmile Matejčić 2, 51000, Rijeka, Croatia

    Ana Meštrović

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  1. Ana Meštrović
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Correspondence to Ana Meštrović .

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Editors and Affiliations

  1. Gdańsk University of Technology, Gdańsk, Poland

    Julian Szymański

  2. Università degli Studi di Trento, Trento, Italy

    Yannis Velegrakis

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Meštrović, A. (2018). Collaboration Networks Analysis: Combining Structural and Keyword-Based Approaches. In: Szymański, J., Velegrakis, Y. (eds) Semantic Keyword-Based Search on Structured Data Sources. IKC 2017. Lecture Notes in Computer Science(), vol 10546. Springer, Cham. https://doi.org/10.1007/978-3-319-74497-1_11

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  • DOI: https://doi.org/10.1007/978-3-319-74497-1_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74496-4

  • Online ISBN: 978-3-319-74497-1

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