Learn how Natural Language Processing (NLP) deciphers sentiment scores in hotel reviews. Discover why phrases like ‘ridiculously high prices’ and ‘cold water’ might lead to a sentiment score of 0.1.
Table of Contents
Question
You are working at the hotel chain. You are planning to apply Natural Language Processing for the sentiment analysis of the customer reviews.
What sentiment score should you expect for the following review: “The prices were ridiculously high. We could stay at the palace for that price! The water in the shower was cold, no hot water whatsoever”?
A. 1
B. 0.5
C. 2
D. 0.9
E. 0.1
Answer
E. 0.1
Explanation
The sentiment analysis score for the given review would likely be around 0.1, indicating a predominantly negative sentiment due to phrases like “ridiculously high prices” and “cold water in the shower.”
Sentiment analysis is producing the sentiment score between 0 and 1. A score close to 0 means a negative sentiment, and close to 1 – positive. And in cases with the neutral or undefined sentiment, the score is 0.5. In this problem, the review is negative, and we should expect a score of 0.1.
All other options are incorrect.
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.
