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Predicting the Evolution of a Constrained Network: A Beta Regression Model

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Data Science

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Abstract

Social network analysis allows to map and measure relationships and flows (links) between people, groups, computers, URLs, or other connected knowledge entities (nodes). In this context, a relevant issue is the treatment of constrained scale-free networks such as the network of student transfers between degree courses offered by an University, that are strongly influenced by a number of institutional decisions. In the analysis of such a system, special attention has to be paid to identify current or future “critical points”, that is nodes characterized by a high number of outcoming or incoming links, on which to act in order to optimize the network. To predict the evolution of a constrained system over time in dependence of constraint modifications, a beta regression model is proposed, that fits links represented by quantities varying between 0 and 1. The algorithm was successfully applied to the network of student transfers within the University of Bologna: the link was defined by the out-transfer rate of the degree course (computed as the ratio of the number of out-transfers to the number of students enrolled) and the critical points of the system were defined by the courses characterized by a high out-transfer rate.

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Authors and Affiliations

  1. Department of Statistical Sciences, University of Bologna, Bologna, Italy

    Luisa Stracqualursi & Patrizia Agati

Authors
  1. Luisa Stracqualursi
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  2. Patrizia Agati
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Corresponding author

Correspondence to Luisa Stracqualursi .

Editor information

Editors and Affiliations

  1. Department of Political Sciences, University of Naples Federico II, Napoli, Italy

    Francesco Palumbo

  2. Department of Statistical Sciences Paolo Fortunati, Alma Mater Studiorum, University of Bologna, Bologna, Italy

    Angela Montanari

  3. Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy

    Maurizio Vichi

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Stracqualursi, L., Agati, P. (2017). Predicting the Evolution of a Constrained Network: A Beta Regression Model. In: Palumbo, F., Montanari, A., Vichi, M. (eds) Data Science . Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-55723-6_26

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