Negation handling in sentiment analysis

Question

I am in need of a little help here, I need to identify the negative words like \"not good\",\"not bad\" and then identify the polarity (negative or positive) of the sentiment. I

Answer 1

this seems to be working decently well as a poor man's word negation in python. it's definitely not perfect, but may be useful for some cases. it takes a spacy sentence object.

def word_is_negated(word):
    """ """

    for child in word.children:
        if child.dep_ == 'neg':
            return True

    if word.pos_ in {'VERB'}:
        for ancestor in word.ancestors:
            if ancestor.pos_ in {'VERB'}:
                for child2 in ancestor.children:
                    if child2.dep_ == 'neg':
                        return True

    return False

def find_negated_wordSentIdxs_in_sent(sent, idxs_of_interest=None):
    """ """

    negated_word_idxs = set()
    for word_sent_idx, word in enumerate(sent):
        if idxs_of_interest:
            if word_sent_idx not in idxs_of_interest:
                continue
        if word_is_negated(word):
            negated_word_idxs.add(word_sent_idx)

    return negated_word_idxs

call it like this:

import spacy
nlp = spacy.load('en_core_web_lg')
find_negated_wordSentIdxs_in_sent(nlp("I have hope, but I do not like summer"))

EDIT: As @Amandeep pointed out, depending on your use case, you may also want to include NOUNS, ADJECTIVES, ADVERBS in the line: if word.pos_ in {'VERB'}:.