Stock sentiment analysis turns unstructured signals — headlines, Reddit threads, analyst notes, Google search spikes — into a numeric read on how the market feels about a company. The premise is simple: prices are set by people, and people leave a paper trail before they trade. Aggregating and scoring that trail can surface shifts in conviction earlier than price alone.
Modern sentiment scoring uses large language models rather than keyword counting. Instead of flagging the word "crash" as negative, a model reads context: "fears of a crash were overblown after earnings beat" is bullish, not bearish. That comprehension is what separates a useful sentiment score from a naive one.
Sentiment is most powerful when it is multi-source and weighted. A single bullish Reddit thread is noise; bullish Reddit activity confirmed by rising news tone and climbing search interest is a signal. Sintinel blends Reddit, financial news, and Google Trends into a single composite so no one source dominates.
Sentiment is a leading indicator, not a crystal ball. It tells you where attention and conviction are moving — pair it with technicals, position sizing, and risk limits before you act. Sentiment that diverges from price (an EV gap) is often where the opportunity lives.