Random Sentiment Analysis Model Selection

This function takes a text input and randomly selects a sentiment analysis model (TextBlob, VADER, or Flair) to analyze the sentiment of the text.

Technology Stack : spaCy, TextBlob, VADER, Flair

Code Type : Function

Code Difficulty : Intermediate

                
                    
def random_sentiment_analysis(text):
    import random
    import spacy

    # Load a pre-trained spaCy model for English
    nlp = spacy.load("en_core_web_sm")

    # Process the text
    doc = nlp(text)

    # Randomly select a sentiment analysis model
    sentiment_models = ["textblob", "vader", "flair"]
    selected_model = random.choice(sentiment_models)

    if selected_model == "textblob":
        from textblob import TextBlob
        analysis = TextBlob(text)
        sentiment = analysis.sentiment.polarity
    elif selected_model == "vader":
        from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
        analyzer = SentimentIntensityAnalyzer()
        sentiment = analyzer.polarity_scores(text)['compound']
    elif selected_model == "flair":
        from flair.models import TextClassifier
        from flair.data import Sentence
        model = TextClassifier.load('en-sentiment')
        sentence = Sentence(text)
        model.predict(sentence)
        sentiment = sentence.labels[0].score

    return sentiment