POS Tagging Valence

In order to determine the POS of Words, the Stanford Grammatical Dependency Parser was used.

#import os
#import numpy as np
#import pandas as pd
#nltk.download()
#import nltk
#import csv
#from nltk.corpus import stopwords
#from nltk.tokenize import word_tokenize, sent_tokenize
#stop_words = set(stopwords.words('english'))

#os.chdir("/Users/lisaherzog/Google Drive/UM/Smart Services/Thesis/Thesis/Code/Feature Set2/Input")

Import Datasets

#Data = pd.read_excel('2.Reviews split into Sentences with stemming.xlsx')
#Text =Data['Review.Fragments'].tolist()

Perform POS Tagging

#TaggedText = []

#for i in range(0,4735):
    #txt = Text[i]
    #tokenized = sent_tokenize(txt)
    
    #for j in tokenized:
        #wordList = nltk.word_tokenize(j)
        #wordList= [w for w in wordList if not w in stop_words]
        #tagged=nltk.pos_tag(wordList)
        #TaggedText.append(tagged)