class_docstr: Give a sentiment intensity score to sentences.
class_docstr_tok: ["Give","a","sentiment","intensity","score","to","sentences","."]
code: def _negation_check(valence, words_and_emoticons, start_i, i):
      words_and_emoticons_lower = [
          str(w).lower() for w in words_and_emoticons
      ]
      if start_i == 0:
          if negated(
              [words_and_emoticons_lower[i - (start_i + 1)]]
          ):  # 1 word preceding lexicon word (w/o stopwords)
              valence = valence * N_SCALAR
      if start_i == 1:
          if words_and_emoticons_lower[i - 2] == "never" and (
              words_and_emoticons_lower[i - 1] == "so"
              or words_and_emoticons_lower[i - 1] == "this"
          ):
              valence = valence * 1.25
          elif (
              words_and_emoticons_lower[i - 2] == "without"
              and words_and_emoticons_lower[i - 1] == "doubt"
          ):
              valence = valence
          elif negated(
              [words_and_emoticons_lower[i - (start_i + 1)]]
          ):  # 2 words preceding the lexicon word position
              valence = valence * N_SCALAR
      if start_i == 2:
          if (
              words_and_emoticons_lower[i - 3] == "never"
              and (
                  words_and_emoticons_lower[i - 2] == "so"
                  or words_and_emoticons_lower[i - 2] == "this"
              )
              or (
                  words_and_emoticons_lower[i - 1] == "so"
                  or words_and_emoticons_lower[i - 1] == "this"
              )
          ):
              valence = valence * 1.25
          elif words_and_emoticons_lower[i - 3] == "without" and (
              words_and_emoticons_lower[i - 2] == "doubt"
              or words_and_emoticons_lower[i - 1] == "doubt"
          ):
              valence = valence
          elif negated(
              [words_and_emoticons_lower[i - (start_i + 1)]]
          ):  # 3 words preceding the lexicon word position
              valence = valence * N_SCALAR
      return valence
  
imports: import os
  import re
  import math
  import string
  import codecs
  import json
  from itertools import product
  from inspect import getsourcefile
  from io import open
label_desc: Use image node_id 10 for calling the SentimentIntensityAnalyzer obj's underlying member method code with example usage: obj._negation_check(valence, words_and_emoticons, start_i, i) and returns: valence