How to extract individual words from sentence and match them with words from pos and neg dictionaries in R [closed]

Answer 1

sent1 = data.frame(Sentences=c("abundant bad abnormal activity was due to 2- face people","strange exciting activity was due to great 2-face people"), user = c(1,2)) 
pos1 = c("abound" , "abounds", "abundant", "exciting", "great")
neg1 = c("2-face","abnormal", "strange", "bad", "weird")

Then I used:

words = (str_split(unlist(sent1$Sentences)," "))

tmp <- data.frame()
tmn <- data.frame()

for (i in 1:nrow(sent1)) {
   for (j in 1:length(words)) {
    for (k in 1:length(pos1)){
     if (words[[i]][j] == pos1[k]) {
    print(paste(i,words[[i]][j],1))
    tmn <- cbind(i,words[[i]][j],1)
    tmp <- rbind(tmp,tmn)
  }
}
for (m in 1:length(neg1)){
  if (words[[i]][j] == neg1[m]) { 
    print(paste(i,words[[i]][j],-1))
    tmn <- cbind(i,words[[i]][j],-1)
    tmp <- rbind(tmp,tmn)
      }
    }  
  }
 }

That resulted into:

print(tmp)
  i       V2 V3
1 1 abundant  1
2 1      bad -1
3 2  strange -1
4 2 exciting  1

If I do something like that:

sent1$Sentences <- as.character(sent1$Sentences)
List <- strsplit(sent1$Sentences, " ")
a <- data.frame(Id=rep(sent1$user, sapply(List, length)),    Words=unlist(List))
a$Words <- as.character(a$Words)
a[a$Words %in% pos1,]

resulted into possitive:

Id    Words
1 abundant
2 exciting
2    great

and negative: a[a$Words %in% neg1,]

Id    Words
1      bad
1 abnormal
1   2-face
2  strange
2   2-face

But I need to add value 1 for possitive and -1 for negative words.

Answer 2

Brute force approach. Not optimal, as uses too many for loops, but seems to be doing what you need. Hopefully, this should be suitable for your application. You can rearrange things or store results in another variable so that the output is w/o [1] [1] etc.

Code:

sent = data.frame(Sentences=c("abundant bad abnormal activity was due to 2-face people","strange exciting activity was due to 2-face people"), user = c(1,2)) 
pos = c("abound" , "abounds", "abundant", "exciting")
neg = c("2-face","abnormal", "strange", "bad", "weird")

words <- matrix(ncol = 2,nrow=8)

words = (str_split(unlist(sent$Sentences)," "))

tmp <- data.frame()
tmn <- data.frame()

for (i in 1:nrow(sent)) {
  for (j in 1:length(words)) {
    for (k in 1:length(pos)){
      if (words[[i]][j] == pos[k]) {
        print(paste(i,words[[i]][j],1))
        tmn <- cbind(i,words[[i]][j],1)
        tmp <- rbind(tmp,tmn)
      }
    }
    for (m in 1:length(neg)){
      if (words[[i]][j] == neg[m]) { 
        print(paste(i,words[[i]][j],-1))
        tmn <- cbind(i,words[[i]][j],-1)
        tmp <- rbind(tmp,tmn)
      }
    }  
  }
}

View(tmp)

Result:

    i   V2         V3
1   1   abundant    1
2   1   bad        -1
3   2   strange    -1
4   2   exciting    1

Answer 3

Will that suit your needs?

pos = c("abound" , "abounds", "abundant")
neg = c("2-face","abnormal")

sent = "abundant abnormal activity was due to 2-face people"

p = 0
for (i in 1:length(pos)) {
  if (grepl(pos[i],sent,ignore.case=T) == TRUE) p = p + 1  
}

n = 0
for (i in 1:length(neg)) {
  if (grepl(neg[i],sent,ignore.case=T) == TRUE) n = n + 1  
}

print(p)
print(n)
print(paste("Overall sentence sentiment score = ", p - n))

Result: positive 1, negative 2, overall -1