Sentiment Analysis.

Sentiment analysis is the use of NLP and machine learning to determine the emotional tone behind text. It can classify content as positive, negative, or neutral, and more advanced models detect specific emotions (joy, anger, frustration) or aspect-level sentiment ('the battery life is great but the camera is poor').

Applications in Digital Marketing

Marketers use sentiment analysis to monitor brand mentions across social media, reviews, and forums; to analyse customer feedback at scale; to track campaign reception; and to identify product or service issues before they escalate. Review platforms and social listening tools are built on sentiment analysis models.

SEO Relevance

Search engines may use sentiment signals from user reviews, comments, and content to evaluate brand reputation and content quality. Positive brand sentiment—measured across reviews, social mentions, and third-party coverage—can correlate with stronger E-E-A-T signals. Monitoring and responding to negative sentiment protects both brand and organic search performance.