Definition
Sentiment in AI answers is how favorably or unfavorably an AI engine describes your brand when it appears in a generated answer — the qualitative complement to mention rate and citation rate. An AI engine might mention your brand frequently but frame it negatively ("Brand X has faced criticism for...") or with hedging ("some users report issues with..."). Sentiment is shaped by the training data the model absorbed and the real-time sources it retrieves: negative reviews on Reddit, critical articles, and complaint threads all feed into how engines characterize your brand. Measuring sentiment requires reading actual AI answers — not just counting mentions — and coding them as positive, neutral or negative. For GEO, sentiment improvement comes from the same evidence-first content strategy that drives citations: publishing specific, verifiable claims with supporting data crowds out vague negative signals with concrete positive evidence. Brands with strong first-party content and third-party endorsements (G2 reviews, press coverage, case studies) consistently earn better sentiment than those relying on marketing copy alone.