可能有一种更优雅的方法可以做到这一点,但这应该可行:
# here I'm generating some example data
set.seed(5)
topic_list1 <- paste(sample(letters, 20, replace=T), sep=";")
topic_list2 <- paste(sample(letters, 15, replace=T), sep=";")
# I don't make the tables right away
tl1 <- unlist(strsplit(topic_list1, split=";"))
tl2 <- unlist(strsplit(topic_list2, split=";"))
big_list <- unique(c(tl1, tl2))
# this computes your frequencies
lbl <- length(big_list)
tMat1 <- matrix(rep(tl1, lbl), byrow=T, nrow=lbl)
tMat2 <- matrix(rep(tl2, lbl), byrow=T, nrow=lbl)
tMat1 <- cbind(big_list, tMat1)
tMat2 <- cbind(big_list, tMat2)
counts1 <- apply(tMat1, 1, function(x){sum(x[1]==x[2:length(x)])})
counts2 <- apply(tMat2, 1, function(x){sum(x[1]==x[2:length(x)])})
total_freqs <- rbind(counts1, counts2, counts1-counts2)
# this makes it nice looking & user friendly
colnames(total_freqs) <- big_list
rownames(total_freqs) <- c("topics1", "topics2", "difference")
total_freqs <- total_freqs[ ,order(total_freqs[3,])]
total_freqs
d l a z b f s y m r x h n i g k c v o
topics1 0 0 0 0 0 2 1 1 1 1 2 2 1 1 1 1 2 2 2
topics2 2 2 2 1 1 2 1 1 1 0 1 1 0 0 0 0 0 0 0
difference -2 -2 -2 -1 -1 0 0 0 0 1 1 1 1 1 1 1 2 2 2
从那里您可以只使用直数或随心所欲地将它们可视化(例如,点图等)。这是一个简单的点图:
windows()
dotchart(t(total_freqs)[,3], main="Frequencies of topics1 - topics2")
abline(v=0)