How to plot the top 10 positive words in a large set of text

positive_dracula.R

library(gutenbergr)
library(tidytext)
library(dplyr)
library(ggplot2)

# Using Dracula as our example text, download it from Project Gutenberg
dracula<-gutenberg_download(345)

# Split each line of text into individual words
dracula<-dracula%>%
  unnest_tokens(word, text)

# Use the Bing sentiment from tidytext and join it to the words in Dracula
bing<-get_sentiments('bing')
dracula<-inner_join(dracula, bing)

# Filter out negative words
dracula<-dracula%>%
  filter(sentiment=='positive')

# Count up the occurrences of each word and arrange them in descending order
# Here we only want the top 10 words
words<-dracula%>%
  group_by(word)%>%
  summarize(count=n())%>%
  arrange(desc(count))%>%
  top_n(10)

# Convert the word field to a factor, so we can preserve our ordering in the plot
words$word<-factor(words$word, levels=words$word)

# Plot the words and counts with ggplot2
ggplot()+
  geom_bar(data=words, aes(x=word,y=count), stat="identity")+
  xlab("Word")+
  ylab("Count")+
  ggtitle("Top 10 Positive words in Dracula")