STA450/650 Theory and Methods for Social Network Analysis

TA for a graduate-level course introducing statistical theory and methods for social network analysis

By Yunran Chen in teaching

January 9, 2019

I served as a teaching assistant, holding a 75-min lab and 2-hr office hour weekly. I prepared a detailed tutorial for my lab and knitted it using bookdown package, which covers the basic network analysis using R.


  • Basic introduction on network objects.
    • R packages including igraph, statnet (including sna, network packages).
  • Collect network data:
    • API requests using R packages (rtweet, Rfacebook, RedditExtractoR, imdbapi, omdbapi).
    • API requests from R directly (rjson, jsonlite)
    • Useful websites: (SNAP, Awesome Network Analysis)
  • Fancy visualization (static and dynamic networks):
    • ggplot2 version: ggnet2, geomnet, ggnetwork
    • Interactive network visualization: ggplot2 + plotly, visNetwork
    • Dynamic network visualization: ggnetwork, ggplot2 + gganimate, ndtv
  • Network analysis using package amen, statnet.
Posted on:
January 9, 2019
1 minute read, 110 words
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