> For the complete documentation index, see [llms.txt](https://docs.tickertrends.io/tickertrends/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tickertrends.io/tickertrends/documentation-v2/2.-data-coverage-and-data-types/2.2-raw-data-types/2.3-social-discussion-analysis/catalyst-detection.md).

# Catalyst detection

The catalyst detection system analyzes social media discussion for a ticker and identifies periods of **significant discussion** that may affect a KPI in the TickerTrends system.

For each detected catalyst, TickerTrends estimates:

* **The likely size of impact**
* **The likely duration of impact**
* **The relevant KPI horizon**

This helps users separate small bursts of noise from discussion that may matter for an earnings period or business metric.

<figure><img src="/files/8s9i3PopVS7DV1txZ0xr" alt=""><figcaption></figcaption></figure>

#### What it shows

Detected catalysts are surfaced as specific social or product events tied to the company. These can include promotions, launches, partnerships, menu changes, creator-driven moments, or broader cultural tie-ins.

Users can quickly see:

* Which catalyst appears most important
* Whether the impact looks temporary or longer lasting
* Which quarter or KPI horizon may be affected

This is especially useful when social momentum builds before the impact is visible in reported financials.