R 词云 - 无法删除英文停用词

Question

在构建词云之前，我尝试从文本中删除英语停用词，但没有奏效。我阅读了几篇文章并尝试了建议的内容，但没有任何运气。任何帮助将不胜感激。

library(tm)
library(wordcloud)
library(RColorBrewer)
library(SnowballC)

textdata <- c(A secur breach expos privat inform of student loan borrow from Aug. 20-22 dure a comput softwar upgrade. User of the DOE Direct Loan Web site were abl to view inform other than their own if they use certain option when access the program web pages. SSNs were among the data element expos online.  Softwar compani Affiliat Comput Servic (ACS) creat the technolog for the Direct Loan Servic featur on the DoE site. )


#Create corpus and clean data
txt <- Corpus(VectorSource(textdata))
txtCorpus <- tm_map(txt, removePunctuation)
txtCorpus <- tm_map(txt, removeNumbers)
txtCorpus <- tm_map(txt, content_transformer(tolower))
txtCorpus <- tm_map(txtCorpus, removeWords, stopwords("english"))
txtCorpus <- tm_map(txt, stripWhitespace); #inspect(docs[1])
txtCorpus <- tm_map(txt, stemDocument)

#Creat tdm
tdm <- TermDocumentMatrix(txtCorpus)
m <- as.matrix(tdm)
v <- sort(rowSums(m),decreasing=TRUE)
d <- data.frame(word = names(v),freq=v, stringsAsFactors = FALSE)
head(d, 10)

输出

        word    freq

the     the     8469        
and     and     5790        
inform  inform  2629        
was     was     2487        
secur   secur   2249        
were    were    1901        
social  social  1890    

Answer 1

修复你的语料库清理：

library(tm)
library(wordcloud)
library(RColorBrewer)
library(SnowballC)
textdata <- c("A secur breach expos privat inform of student loan borrow from Aug. 20-22 dure a comput softwar upgrade. User of the DOE Direct Loan Web site were abl to view inform other than their own if they use certain option when access the program web pages. SSNs were among the data element expos online.  Softwar compani Affiliat Comput Servic (ACS) creat the technolog for the Direct Loan Servic featur on the DoE site. ")
corp <- Corpus(VectorSource(textdata))
corp <- tm_map(corp, removePunctuation)
corp <- tm_map(corp, removeNumbers)
corp <- tm_map(corp, content_transformer(tolower))
corp <- tm_map(corp, removeWords, stopwords("english"))
corp <- tm_map(corp, stripWhitespace); #inspect(docs[1])
corp <- tm_map(corp, stemDocument)

tdm <- TermDocumentMatrix(corp)
m <- as.matrix(tdm)
v <- sort(rowSums(m),decreasing=TRUE)
d <- data.frame(word = names(v),freq=v, stringsAsFactors = FALSE)
head(d, 10)
#            word freq
# loan       loan    3
# comput   comput    2
# direct   direct    2
# doe         doe    2
# expo       expo    2
# inform   inform    2
# servic   servic    2
# site       site    2
# softwar softwar    2
# web         web    2