Negations POS Tagging

Purpose

Once the negation tag has been added to words, the the remaining text was exported for further POS Tagging. The following subsection provides an overview on the POS Tagging process.

Preparation

#import os
#import numpy as np
#import pandas as pd
#nltk.download()

#os.chdir("/Users/lisaherzog/Google Drive/UM/Smart Services/Thesis/Thesis/Code/Feature Set3/Input")

Import Data

Import NLTK

#import nltk
#from nltk.corpus import stopwords
#from nltk.tokenize import word_tokenize, sent_tokenize
#stop_words = set(stopwords.words('english'))

Perform POS Tagging

#PosTagging=[]

#for i in range(0,4735):
    #txt = Text[i]
    #tokenized = sent_tokenize(txt)
    #taggedtokens =[]
    #PosTagging.append(taggedtokens)
    
    #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)
        #taggedtokens.append(tagged)

#PosTaggedText = []

#for j in range(0,4735):
    #Review = PosTagging[j]
    #Review = sum(Review,[])
    #PosTaggedText.append(Review)