Create Data Set; Using the text mining analysis method produced by NVivo and RStudio which extracts it automatically with a series of algorithms to convert unstructured text into structured data and produce numeric data. 
x1 <-c(1,2,3,4,5,6,7,8,9,10,
       11,12,13,14,15,16,17,18,19,20)
y1 <-c(90,84,57,25,42,35,29,25,43,24,24,20,19,18,16,16,15,13,12,7)
label1<-c('Sept','Rebellion','Resurrection','Rise','Film',
          'Rejection','Dark','Murder','Action','Forbidden',
          'Cruelty','Danger','Forbin','Threat','Contary',
          'Betrayal','Coup','Mastermind','Kidnapping','Overthrow')
The data above comes from 200 Indonesian media framings about communism which were then investigated through anti-communist narratives.

Data Frame

againts.data <-data.frame(x1, y1, label1)

Create Text Analyst

library(ggplot2)
library(ggrepel)

ggplot(data = againts.data, aes(x=x1, y=y1))+
  geom_point(color ="red", size =3)+
  ylab("Code Propaganda")+
  xlab("Index")+
geom_text_repel(aes(label= label1),
        box.padding =0.35,
        point.padding =0.5,
        segment.color = 'grey50') +
theme_classic()