# Load sentiment analysis model
sentiment_analyzer = pipeline("sentiment-analysis")
# Sample support tickets
tickets = [
"I'm furious! My product arrived broken!",
"I'm so happy with the service, thank you!",
"The website is not working, and I can't log in."
]
# Analyze sentiment and classify urgency
for ticket in tickets:
sentiment = sentiment_analyzer(ticket)[0]
urgency = "High" if sentiment["label"] == "NEGATIVE" else "Low"
print(f"Ticket: {ticket}\nSentiment: {sentiment['label']}, Urgency: {urgency}\n")
Sentiment Analysis: Classify support tickets or social media feedback to prioritize responses.
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