TikTok ad library scraping and trend analysis
Scrape and classify TikTok's public ad library to identify trending music, sounds, effects, hashtags, and creative hooks in viral ad campaigns
XNot a typed-decision job: needs written output, plain rules or lookups would do it, or needs raw image or audio. Also marks ideas that must not be built.4.30
Key facts
- Vertical
- Agencies, media & creators
- Function
- Ads
- Status
- Seen in the wild
- Volume
- routine
- Value
- meaningful
- Risk
- moderate
- Evidence
- described plan
- Flags
- check-fit
Source: https://docs.ninjacat.io/changelog/ad-library-tiktok-and-linkedin-added
Build this with a classifier
Define a typed decision with a bounded answer, then evaluate it on examples.
{
"decision_type": "choice",
"question": "Does this input match the decision in “TikTok ad library scraping and trend analysis”?",
"input": "<input to classify>",
"output": "one label from a fixed list"
}Related use cases
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