Wouter van Atteveldt
Session 6: Semantic Networks and Visualization
Thursday: Introduction to R
Friday: Corpus Analysis & Topic Modeling
Saturday:
Sunday:
plot(x=.., y=..)
plot(lm(d$y ~ d$x))
plot(d$y~d$x)
plot(d)
lines(x, y)
abline(v=v)
abline(lm(..))
legend(..)
title(..)
axis(..)
ggplot plots are composed of layers:
+
:ggplot(data, aes(.)) + geom_line(.) + ...
dygraphs: interactive time series
See also: http://www.r-graph-gallery.com/
Visualization with R
Thursday: Introduction to R
Friday: Corpus Analysis & Topic Modeling
Saturday:
Sunday:
semnet
github.com/kasperwelbers/semnet
library(semnet)
g = coOccurenceNetwork(dtm)
g = windowedCoOccurenceNetwork(location, term, context)
igraph
E(g)$label
, etcg_backbone = getBackboneNetwork(g, alpha=0.01, max.vertices=100)
write.graph(g, filename, format)
library(rgexf)
gefx = igraph.to.gexf(g)
print(gefx, file="..")
Semantic Network Analysis
Break
Hand-outs:
What you have learned:
Go out and code!