> For the complete documentation index, see [llms.txt](https://quanthiveai.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://quanthiveai.gitbook.io/docs/social-sentiment-trading-signals-coming-soon.md).

# Social Sentiment Trading Signals (Coming Soon)

QuantHive’s upcoming **Social Sentiment Trading Signals**, powered by AWS, will bring real-time market sentiment analysis to your trading toolkit. This system scans thousands of social and news sources using advanced AI to detect shifts in mood, hype cycles, and trending narratives across crypto communities.

Each token will be assigned a **Sentiment Score from 0 to 100**, where:

* **<50** indicates bearish sentiment
* **>50** indicates bullish sentiment

## What Sets It Apart

On top of just a numerical score, QuantHive’s AI will also perform **qualitative analysis** to explain the *why* behind the sentiment. This includes:

* Summarizing key narratives or catalysts (e.g., token unlocks, partnerships, AI hype)
* Highlighting recurring community opinions and narratives
* Surfacing notable influencer commentary driving the sentiment shift

This gives users **contextual insight**, not just a number, helping traders understand the underlying market psychology.

## What to Expect

* **AI-powered NLP** scanning major social platforms, news, and forums
* **Sentiment Scoring** to help quantify market mood in real time
* **Narrative detection** to track tokens tied to rising themes like AI, RWA, or memecoins
* **Integrated Signals** to combine with Alpha Trader data for well-rounded trading decisions

Once live, this signal will give traders early insight into crowd psychology and public perception — a critical edge in fast-moving markets. Used alongside on-chain alpha data like TPI and Momentum, it will help confirm entries, exits, or reinforce conviction in a trade.