Sentiment analysis is a natural language processing technique that determines the positive, negative, or neutral sentiment of text data like customer reviews. Learn how it’s used in Microsoft Azure AI solutions and why it’s a key concept for the Azure AI Fundamentals AI-900 certification exam.
Table of Contents
Question
You are developing a natural language processing solution in Azure for following use case:
The solution should analyze customer reviews and determine how positive or negative each review is. This is an example of which type of natural language processing workload?
A. key phrase extraction.
B. sentiment analysis.
C. language detection.
D. entity recognition.
Answer
B. sentiment analysis.
Explanation
Sentiment analysis is the correct answer to this question. Sentiment analysis is a natural language processing (NLP) technique that analyzes text data to determine the overall sentiment, opinion, or emotional tone, classifying it as positive, negative or neutral.
In the given scenario of analyzing customer reviews to gauge how positive or negative each one is, sentiment analysis is the most applicable NLP workload. It allows you to automatically process large volumes of opinion-based text data and understand the overall sentiment expressed.
The other options are useful NLP techniques but would not directly solve the use case:
A. Key phrase extraction identifies the main topics and themes but doesn’t assess sentiment.
C. Language detection determines the language of the text but not the opinion expressed.
D. Entity recognition finds named entities like people, places, and organizations rather than analyzing sentiment.
So in summary, choice B, sentiment analysis, is the best fit for automatically determining how positive or negative each customer review is in this Azure NLP solution. It’s a fundamental NLP concept to understand for the AI-900 Azure AI Fundamentals certification exam.
This is because sentiment analysis is used to determine whether the sentiment expressed in a piece of text (such as a customer review) is positive, negative, or neutral. It is a common use case in natural language processing for analyzing opinions and emotions in text.
Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.