Applying a function to values from two data frames simultaneously, to generate a third

Question

Apologies if this turns out to be a very specific problem, which may not generalise to that of others'.

Background

I hope to do some sentiment analysis, starting from the basic binary matching of words from a lexicon, and then moving towards some more complex form of Sentiment Analysis, making use of grammatical rules, etc.

Problem

To do some binary matching - which will form the first phase of Sentiment Analysis - I am provided with two tables, one containing words, and the other containing Parts-Of-Speech for these words.

    V1     V2        V3          V4   V5
1    R     is fantastic    language <NA>
2 Java     is       far        from good
3 Data mining        is fascinating <NA>


   V1  V2  V3 V4   V5
1  NN VBZ  JJ NN <NA>
2 NNP VBZ  RB IN   JJ
3 NNP  NN VBZ JJ <NA>

I would like to carry out some basic Sentiment Analysis as follows: I want to apply a function that takes two arguments, a word (from the 1st data frame) and its corresponding POS tag (from the second) to determine which list words to use in determining positive/negative orientation of a word. For example, the word fantastic would be extracted along with the POS tag 'JJ', and so the list of adjectives alone would be inspected for presence/absence of this word.

Eventually, I would like to end up with a data frame that shows the result of matching:

   V1  V2  V3 V4   V5
1  0   0   1   0   <NA>
2  0   0  -1   0   1
3  0   0   0   1   <NA>

I tried formulating my own code, but kept getting an error, after which I felt this was not going to work.

#test sentences
sentences<- as.list(c("R is fantastic language", "Java is far from good", "Data mining is fascinating"))

#using the OpenNLP package
require(openNLP)

#perform tagging
taggedSentences<- tagPOS(sentences)

#split to words
individualWords<- unname(sapply(taggedSentences, function(x){strsplit(x,split=" ")}))

#Strip Tags
individualWordsClean<- unname(sapply(individualWords, function(x){gsub("/.+","",x)}))

#Strip words
individualTags<- unname(sapply(individualWords, function(x){gsub(".+/","",x)}))

#create a dataframe for words; courtesy @trinker
numberRow<- length(individualWords)
numberCol<- unname(sapply(individualWords, length))
df1<- as.data.frame(matrix(nrow=numberRow, ncol=max(numberCol)))
for (i in 1:numberRow){
df1[i,1:numberCol[i]]<- individualWordsClean [[i]]
}


#create a dataframe for tags; courtesy @trinker
numberRow<- length(individualWords)
numberCol<- unname(sapply(individualTags, length))
df2<- as.data.frame(matrix(nrow=numberRow, ncol=max(numberCol)))
for (i in 1:numberRow){
df2[i,1:numberCol[i]]<- individualTags [[i]]
}

#Create negative/positive words' lists
posAdj<- c("fantastic","fascinating","good")
negAdj<- c("bad","poor")
posNoun<- "R"
negNoun<- "Java"

#Function to match words and assign sentiment score
checkLexicon<- function(word,tag){
if (grep("JJ|JJR|JJS",tag)){
ifelse(word %in% posAdj, +1, ifelse(word  %in% negAdj, -1, 0))
}
else if(grep("NN|NNP|NNPS|NNS",tag)){
ifelse(word %in% posNoun, +1, ifelse(word %in% negNoun, -1, 0))
}
else if(grep("VBZ",tag)){
ifelse(word %in% "is","ok","none")
}
else if(grep("RB",tag)){
ifelse(word %in% "not",-1,0)
}
else if(grep("IN",tag)){
ifelse(word %in% "far",-1,0)
}
}

#Method to output a single value when used in conjuction with apply
justShow<- function(x){
    x
    }

#Main method that intends to extract word/POS tag pair, and determine sentiment score
mapply(FUN=checkLexicon, word=apply(df1,2,justShow),tag=apply(df2,2,justShow))

Unfortunately, I have had no success with this method, and the error received is

Error in if (grep("JJ|JJR|JJS", tag)) { : argument is of length zero

I am relatively new to R, but it seems that I am unable to use the apply function here, as it returns no argument to the mapply function. Also, I am not sure if mapply will actually produce another data frame.

Please do criticise/advise. Thanks

PS. Link to TRinker's notes on R for those interested.

Answer 1

The mistake was attempting to use grep as grepl. This was corrected after Joran pointed it out. The working function is as follows.

>df1

    V1     V2        V3          V4   V5
1    R     is fantastic    language <NA>
2 Java     is       far        from good
3 Data mining        is fascinating <NA>

>df2

   V1  V2  V3 V4   V5
1  NN VBZ  JJ NN <NA>
2 NNP VBZ  RB IN   JJ
3 NNP  NN VBZ JJ <NA>

#Function to match words and assign sentiment score
checkLexicon<- function(word,tag){
if (grepl("JJ|JJR|JJS",tag)){
ifelse(word %in% posAdj, +1, ifelse(word  %in% negAdj, -1, 0))
}
else if(grepl("NN|NNP|NNPS|NNS",tag)){
ifelse(word %in% posNoun, +1, ifelse(word %in% negNoun, -1, 0))
}
else if(grepl("VBZ",tag)){
ifelse(word %in% "is","ok","none")
}
else if(grepl("RB",tag)){
ifelse(word %in% "not",-1,0)
}
else if(grepl("IN",tag)){
ifelse(word %in% "far",-1,0)
}
}

#Method to output a single value when used in conjuction with apply
justShow<- function(x){
    x
    }

#Main method that intends to extract word/POS tag pair, and determine sentiment score
myObject<- mapply(FUN=checkLexicon, word=apply(df1,2,justShow),tag=apply(df2,2,justShow))

#Shaping the final dataframe
scoredDF<- as.data.frame(matrix(myObject,nrow=3))

  V1 V2 V3 V4   V5
1  1 ok  1  0 NULL
2 -1 ok  0  0    1
3  0  0 ok  1 NULL