This is the first in a series of chapters on text analysis. One frequent focus of social media and customer review analysis is understanding the emotional tone behind the text. Chapter 10 introduces sentiment analysis as a technique to gauge opinions ranging from negative to positive and emotion analysis, which captures specific feelings like joy or anger. The chapter explores sentiment analysis levels, including document, sentence, and aspect-based approaches, and compares lexicon-based methods with machine learning techniques. The chapter then discusses frequently used tools such as VADER, TextBlob, and SentiStrength, comparing their advantages and disadvantages. The practical assignment uses an AI Assistant to develop Python code for detecting the sentiment expressed towards COVID-19 vaccines in social media. The lab then compares the performance of multiple models, thereby reinforcing the knowledge of model validation and evaluation from Chapter 8 .