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Do-it-yourself networks: a novel method of generating weighted networks
Author(s) -
David W. Shanafelt,
Kehinde R. Salau,
Jacopo A. Baggio
Publication year - 2017
Publication title -
royal society open science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 51
ISSN - 2054-5703
DOI - 10.1098/rsos.171227
Subject(s) - computer science , data science , ecology , social network (sociolinguistics) , social network analysis , management science , engineering , biology , world wide web , social media
Network theory is finding applications in the life and social sciences for ecology, epidemiology, finance and social–ecological systems. While there are methods to generate specific types of networks, the broad literature is focused on generating unweighted networks. In this paper, we present a framework for generating weighted networks that satisfy user-defined criteria. Each criterion hierarchically defines a feature of the network and, in doing so, complements existing algorithms in the literature. We use a general example of ecological species dispersal to illustrate the method and provide open-source code for academic purposes.

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