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How can I implement sentiment analysis in a chatbot conversation?
Asked on Nov 20, 2025
Answer
To implement sentiment analysis in a chatbot conversation, you can integrate an NLP library or API that provides sentiment analysis capabilities, such as OpenAI or a Python library like TextBlob. This allows the chatbot to analyze user input and respond appropriately based on the detected sentiment.
<!-- BEGIN COPY / PASTE -->
import openai
def analyze_sentiment(user_input):
response = openai.Completion.create(
engine="text-davinci-003",
prompt=f"Analyze the sentiment of the following text: {user_input}",
max_tokens=10
)
sentiment = response.choices[0].text.strip()
return sentiment
<!-- END COPY / PASTE -->Additional Comment:
- Sentiment analysis helps tailor chatbot responses to user emotions, improving user experience.
- Ensure your chatbot platform supports integration with external APIs or libraries for seamless implementation.
- Consider using pre-trained models or services to save time and resources.
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