text processign for sentiment analysis

TRIDEEP SAHA answered on February 5, 2024 Popularity 6/10 Helpfulness 1/10

answer text processign for sentiment analysis

text processign for sentiment analysis

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# Convert to lowercase, and remove stop words

def remove_links(text):
    # Remove any hyperlinks that may be in the text starting with http
    import re
    return re.sub(r"http\S+", "", text)

def style_text(text:str):
    # Convert to lowercase
    return text.lower()

def remove_words(text_data:str,list_of_words_to_remove: typing.List):
    # Remove all words as specified in a custom list of words
    return [item for item in text_data if item not in list_of_words_to_remove]

def collapse_list_to_string(string_list):
    # This is to join back together the text data into a single string
    return ' '.join(string_list)

def remove_apostrophes(text):
    # Remove any apostrophes as these are irrelavent in our word cloud
    text = text.replace("'", "")
    text = text.replace('"', "")
    text = text.replace('`', "")
    return text


text_data['cleaned_text'] = text_data[0].astype(str).apply(remove_links)

text_data['cleaned_text'] = text_data['cleaned_text'].astype(str).apply(style_text)

text_data['cleaned_text'] = text_data['cleaned_text'].astype(str).apply(lambda x: remove_words(x.split(),stopcorpus))

text_data['cleaned_text'] = text_data['cleaned_text'].apply(collapse_list_to_string)

text_data['cleaned_text'] = text_data['cleaned_text'].apply(remove_apostrophes)

display(text_data['cleaned_text'].head(5))

Popularity 6/10 Helpfulness 1/10 Language python

Source: jackmckew.dev

Tags: python sentiment-analysis text

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Contributed on Feb 05 2024

TRIDEEP SAHA

0 Answers Avg Quality 2/10

text processign for sentiment analysis

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