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Representing and Analysing Purposiveness with SNA

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Learning Analytics in R with SNA, LSA, and MPIA

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Abstract

Social Network Analysis is a powerful instrument for representing and analysing networks and the relational structure expressed in the incidences from which they are constructed. This chapter provides an introduction (including data preparation) to the available analytical instruments. Both a foundational and an extended application example demonstrate how (social) network analysis is applied in practice.

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Notes

  1. 1.

    A more simplified version of this example is made available by the author of this book online:http://crunch.kmi.open.ac.uk/people/~fwild/services/simple-sna.Rmw

  2. 2.

    Legacy systems are, e.g., the exam database of the learning management system of the Open University mentioned in the example above.

  3. 3.

    The example presented has been made available by the author of this book on CRUNCH under the following URL: http://crunch.kmi.open.ac.uk/people/~fwild/services/forum-sna.Rmw

  4. 4.

    More efficient (but for here also more complicated) would be to multiply the original adjacency matrix with an inverted diagonal matrix, thereby removing values from the diagonal.

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Authors and Affiliations

  1. Performance Augmentation Lab Department of Computing and Communications Technologies, Oxford Brookes University, Oxford, UK

    Fridolin Wild

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  1. Fridolin Wild
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Wild, F. (2016). Representing and Analysing Purposiveness with SNA. In: Learning Analytics in R with SNA, LSA, and MPIA. Springer, Cham. https://doi.org/10.1007/978-3-319-28791-1_3

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  • DOI: https://doi.org/10.1007/978-3-319-28791-1_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28789-8

  • Online ISBN: 978-3-319-28791-1

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