Spanish Discourses _Pg6

6. Cluster from CA coordinates (three factors ncp=3). Words

Hierarchical Agglomerative Clustering without Contiguity-Constrained

res.HCca <- LexHCca(resLexCA, cluster.CA="words", nb.clust=5, graph=FALSE)
plot(res.HCca)

## Warning: ggrepel: 1026 unlabeled data points (too many overlaps). Consider increasing max.overlaps

To avoid the problem:

“Warning: ggrepel: 1026 unlabeled data points (too many overlaps). Consider increasing max.overlaps”

plot(res.HCca, plot=c("labels"), labels=c(max.overlaps=Inf))

Labels without reppel

plot(res.HCca, plot=c("labels"), labels=c(size=4, force=0))

50 words with highest coordinates

plot(res.HCca, plot="labels", selInd="coord 50", labels=c(max.overlaps=Inf))

Selecting words

plot(res.HCca, plot="labels", selInd=c("España","españoles", "españolas"), labels=(force=0))

 

Selecting one cluster

plot(res.HCca, plot="labels", selClust=c(1), labels=c(force=0), xlim=c(-1.2,0), ylim=c(-1.2,.2))

Using max.overlaps:

plot(res.HCca, plot="labels", selClust=c(1), labels=c(max.overlaps=Inf), xlim=c(-1.2,0), ylim=c(-1.2,.2))

plot(res.HCca, plot="labels", selClust=c(1), selInd="contrib .2", labels=c(force=0.3, max.overlaps=Inf), xlim=c(-1,0), ylim=c(-1.2,0))