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2 results

  • 8 - Working with Network Data in R

  • Jennifer M. Larson, Vanderbilt University, Tennessee
  • Book:
    Designing Empirical Social Networks Research
    Published online:
    07 November 2024
    Print publication:
    21 November 2024, pp 113-142

  • Summary

    Once the data are collected and cleaned, we can start to explore features of the network. Taking an initial look at descriptive network statistics is a good way to take an overview of the data and to spot red flags that signal a problem with the data entry or cleaning. The earlier these can be identified, the better. This chapter serves as a tutorial for using R to do so using the igraph package. It introduces the process of importing a data file into R and walks through the first things you might do with the data, including computing descriptive statistics of the structural features, integrating substantive features of nodes and links, and visualizing the network.

  • Using R to Build and Assess Network Models inBiology

  • G. Hartvigsen
  • Journal:
    Mathematical Modelling of Natural Phenomena / Volume 6 / Issue 6 / 2011
    Published online by Cambridge University Press:
    05 October 2011, pp. 61-75
    Print publication:
    2011

  • In this paper we build and analyze networks using the statistical and programmingenvironment R and the igraph package. We investigate random, small-world, and scale-freenetworks and test a standard problem of connectivity on a random graph. We then develop amethod to study how vaccination can alter the structure of a disease transmission network.We also discuss a variety of other uses for networks in biology.