Sentiment Analysis with spaCy

This function uses the spaCy library to analyze the sentiment of the input text and returns the sentiment result (positive, negative, or neutral).

Technology Stack : spaCy

Code Type : Function

Code Difficulty : Intermediate

                
                    
import spacy
from spacy.tokens import Doc

def analyze_text_sentiment(text):
    # Load English tokenizer, tagger, parser, NER and word vectors
    nlp = spacy.load('en_core_web_sm')
    
    # Process whole documents
    doc = nlp(text)
    
    # Analyze sentiment
    sentiment_score = 0
    for token in doc:
        if token.sentiment:
            sentiment_score += token.sentiment
    
    # Determine overall sentiment based on the average score
    if sentiment_score > 0:
        overall_sentiment = 'Positive'
    elif sentiment_score < 0:
        overall_sentiment = 'Negative'
    else:
        overall_sentiment = 'Neutral'
    
    return overall_sentiment