posinega

library(RMeCab)
library(knitr)

pndic <- read.table(
  "http://www.lr.pi.titech.ac.jp/~takamura/pubs/pn_ja.dic",
  sep = ":",
  col.names = c("term", "kana", "pos", "value"),
  colClasses = c("character", "character", "factor", "numeric"),
  fileEncoding = "Shift_JIS")
str(pndic)

## 'data.frame':    55125 obs. of  4 variables:
##  $ term : chr  "優れる" "良い" "喜ぶ" "褒める" ...
##  $ kana : chr  "すぐれる" "よい" "よろこぶ" "ほめる" ...
##  $ pos  : Factor w/ 5 levels "形容詞","助動詞",..: 3 1 3 3 1 1 1 3 5 3 ...
##  $ value: num  1 1 1 1 1 ...

pndic2 <- aggregate(value ~ term + pos, pndic, mean)
str(pndic2)

## 'data.frame':    52689 obs. of  3 variables:
##  $ term : chr  "あくどい" "あざとい" "あたじけない" "あっけ" ...
##  $ pos  : Factor w/ 5 levels "形容詞","助動詞",..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ value: num  -0.991 -0.983 -0.993 -0.976 0.993 ...

tw1 <- "すもももももももものうち"
tw2 <- "今日もしんどい"
tw <- c(tw1,tw2)
tw.pn <- c()
for(i in 1:2){
  tmp <-data.frame(
    term = unlist(RMeCabC(tw[i])),
    pos = attr(unlist(RMeCabC(tw[i])),"names"))
  tw.pn[i] <- sum(merge(tmp, pndic2, 
              by.x = c("term", "pos"), by.y = c("term", "pos"))[,3])
}
kable(data.frame(text = tw, score = tw.pn))

text	score
すもももももももものうち	0.0000000
今日もしんどい	-0.7757595