What is Sentiment corpus?

The sentiment corpus is the body of third-party opinion an AI engine can index about a brand — the reviews, community threads, forum posts, social discussion, and editorial coverage whose aggregate tone and specificity feed the engine’s recommendation decision.

It is read as sentiment-weighted rather than as a raw count: a small, strongly positive, use-case-specific corpus can win a recommendation in a niche because the engine has consistent evidence to quote, while a large corpus with a loud negative strand often loses to a cleaner competitor because the engine surfaces the controversy and hedges. Recency matters as much as tone — a corpus that was positive two years ago but has gone quiet reads as stale and gets down-weighted on time-sensitive commercial queries, the same way stale pages are. The strongest sentiment-corpus asset is a recent body of explicit ‘I use this for X and it’s great because Y’ language, because it maps directly onto the ‘best X for Y’ queries where recommendations are made. Optimizing the sentiment corpus therefore means producing recent, specific, net-positive opinion at enough volume to look non-anecdotal — a very different program from simply ‘getting more reviews’.