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ZENODO
Software . 2018
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agreenville/Bipartite-Network: Bipartite Network Analysis

Authors: Greenville, Aaron;

agreenville/Bipartite-Network: Bipartite Network Analysis

Abstract

Bipartite Network Analysis The Bipartite Network analysis app was created with Shiny and Bipartite package for R. The app was made to visualise a bipartite network and generate nestedness indices for student projects. Features: Supports data matrices with and without abundance data of lower-order group/species. Generates bipartite graph from interaction matrix. Calculates nestedness (NODF2) indices. Visualises interaction matrix. Shading indicates number of interactions. Download graphs and matrices and save to your device. Data file format: Save data file as a .csv, with rows as higher order group (e.g. plant species) and columns as lower order group (e.g. invertebrate species). If you have the abundance of each higher order group (e.g. plant species), add abundance data as the last column. You can see the app in action here: https://aaronecology.shinyapps.io/Network/ Example datasets from the Bipartite package: Safariland.csv Safariland_Abund.csv (has plant abundance data in the last column)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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