This document discusses sentiment analysis and different approaches for measuring sentiment at scale. It explains that while crowdsourcing is slow and expensive, machines can be taught to analyze sentiment through machine learning by training them on large amounts of human-tagged text. However, accuracy depends on the type of language and domain. The best approach is typically a combination of machine analysis for large volumes supplemented by manual review of important texts.