First shot: Sentiment Analysis in R #2.R

#load up word polarity list and format it
afinn_list <- read.delim(file='AFINN/AFINN-111.txt', header=FALSE, stringsAsFactors=FALSE)
names(afinn_list) <- c('word', 'score')
afinn_list$word <- tolower(afinn_list$word)

#categorize words as very negative to very positive and add some movie-specific words
vNegTerms <- afinn_list$word[afinn_list$score==-5 | afinn_list$score==-4]
negTerms <- c(afinn_list$word[afinn_list$score==-3 | afinn_list$score==-2 | afinn_list$score==-1], "second-rate", "moronic", "third-rate", "flawed", "juvenile", "boring", "distasteful", "ordinary", "disgusting", "senseless", "static", "brutal", "confused", "disappointing", "bloody", "silly", "tired", "predictable", "stupid", "uninteresting", "trite", "uneven", "outdated", "dreadful", "bland")
posTerms <- c(afinn_list$word[afinn_list$score==3 | afinn_list$score==2 | afinn_list$score==1], "first-rate", "insightful", "clever", "charming", "comical", "charismatic", "enjoyable", "absorbing", "sensitive", "intriguing", "powerful", "pleasant", "surprising", "thought-provoking", "imaginative", "unpretentious")
vPosTerms <- c(afinn_list$word[afinn_list$score==5 | afinn_list$score==4], "uproarious", "riveting", "fascinating", "dazzling", "legendary")