Sentiment Analysis with TextBlob
This guide demonstrates how to perform simple sentiment analysis on text using the TextBlob library. TextBlob provides a simple API for diving into common natural language processing (NLP) tasks.
Modules Used:
textblob: For processing textual data.- argparse: To handle command-line arguments.
Installation
pip install textblob
python -m textblob.download_corporaThe Code
Save this as sentiment.py.
from textblob import TextBlob
import argparse
def analyze_sentiment(text):
print(f"Analyzing: \"{text}\"\n")
blob = TextBlob(text)
# Polarity: Float within the range [-1.0, 1.0]
# -1.0 is very negative, 1.0 is very positive
polarity = blob.sentiment.polarity
# Subjectivity: Float within the range [0.0, 1.0]
# 0.0 is very objective, 1.0 is very subjective
subjectivity = blob.sentiment.subjectivity
print(f"Polarity: {polarity:.2f}", end=" ")
if polarity > 0.1:
print("(Positive)")
elif polarity < -0.1:
print("(Negative)")
else:
print("(Neutral)")
print(f"Subjectivity: {subjectivity:.2f}", end=" ")
if subjectivity > 0.5:
print("(Subjective/Opinion)")
else:
print("(Objective/Fact)")
# Sentence-level analysis
if len(blob.sentences) > 1:
print("\nSentence Breakdown:")
for sentence in blob.sentences:
print(f" - \"{sentence}\" (Polarity: {sentence.sentiment.polarity:.2f})")
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="TextBlob Sentiment Analyzer")
parser.add_argument("text", help="Text to analyze")
args = parser.parse_args()
analyze_sentiment(args.text)Usage
# Analyze a simple sentence
python sentiment.py "I love programming in Python. It is amazing."
# Analyze a negative sentence
python sentiment.py "This is the worst experience I have ever had."