Microsoft Azure AI Fundamentals (AI-900) Practice Exam 2025 – The Complete Resource to Master Your Certification!

The technique used to assess whether a review is positive or negative is sentiment analysis. This method involves analyzing text data to determine the emotional tone or sentiment expressed within it. It applies natural language processing (NLP) technologies to process and analyze the words, phrases, and context of the review. By identifying keywords, phrases, and patterns, sentiment analysis can categorize the sentiment expressed as positive, negative, or neutral.

While natural language processing is a foundational element of sentiment analysis and is used to interpret and analyze the text, sentiment analysis specifically focuses on the task of gauging emotional sentiment. Thus, while both options involve NLP, sentiment analysis more directly addresses the evaluation of opinions within text, making it the most suitable choice for assessing the polarity of reviews.

Time series analysis is used to analyze data points collected or recorded at specific time intervals, often used for forecasting or trend analysis, and data visualization is a technique for representing data graphically to discern patterns, but these do not pertain to sentiment assessment directly.