What is sentiment analysis and how does it apply to reputation?

Sentiment analysis is the classification of content by tone – positive, neutral, or negative – and in reputation work it is the mechanism that turns a sea of text into a measurable signal. It is applied across the layers that matter: the URLs ranking for branded queries, so the page-one picture can be scored; the responses the AI engines give about the entity, so the narrative can be tracked by tone; and key stakeholder communications, where relevant. The value is in the aggregate and the trend, not any single classification – it shows how the overall tone of the result set or the AI narrative is moving over time, and whether an intervention shifted it. The honest caveat is that automated sentiment classification is imperfect on nuance, sarcasm, and context, so it is treated as a directional measure read alongside human judgment rather than as ground truth. Used that way, it is a useful instrument for seeing whether reputation work is changing perception. We apply sentiment analysis within IMPACT™ for search and AIQ™ for the AI engines, tracking trend and intervention impact.