tiktok/analytics/detect-fake-views
Analyze TikTok video traffic data using advanced algorithms to precisely detect potential fake views and unnatural engagement Evaluate content authenticity and traffic quality based on TikTok's Traffic Pool theory Provid...
Example output — click Run to generate your own
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OpenAI-compatible endpoint with unified authentication and usage tracking.
https://api.sandbase.ai/v1/runtiktok/analytics/detect-fake-viewsInput Schema
2 parameters · 1 required · 1 optional
| Parameter | Type | Required | Description |
|---|---|---|---|
item_id | string | Required | Video ID, required parameter, can be extracted from video URL (e.g., 7460937381265411370 from https://www.tiktok.com/@tiktok/video/7460937381265411370) |
content_category | string | Optional | Content category, optional parameter, affects engagement rate benchmarks, options include: |
Output Schema
| Field | Type | Description |
|---|---|---|
id | string | Unique identifier for the generation task |
status | string | Task status: pending, running, completed, failed, timeout |
model | string | Model used for the generation |
outputs | array | Array of output items |
outputs[].url | string | URL of the generated artifact |
outputs[].content_type | string | MIME type (e.g. image/png, video/mp4) |
error | object | null | Error details if failed, null on success |
error.type | string | Machine-readable error type code |
error.message | string | Human-readable error description |
Code Examples
Ready-to-run snippets
curl -X POST https://api.sandbase.ai/v1/run \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "tiktok/analytics/detect-fake-views",
"prompt": "a beautiful sunset over mountains"
}'API README
Detect fake views in video
Analyze TikTok video traffic data using advanced algorithms to precisely detect potential fake views and unnatural engagement Evaluate content authenticity and traffic quality based on TikTok's Traffic Pool theory Provide comprehensive fraud risk analysis with in-depth assessment across 8 dimensions and 20+ metrics Deliver professional traffic quality reports and optimization recommendations for creators, MCN agencies, and content managers. It is suitable for tiktok workflows.
Capability
Analyze TikTok video traffic data using advanced algorithms to precisely detect potential fake views and unnatural engagement Evaluate content authenticity and traffic quality based on TikTok's Traffic Pool theory Provide comprehensive fraud risk analysis with in-depth assessment across 8 dimensions and 20+ metrics Deliver professional traffic quality reports and optimization recommendations for creators, MCN agencies, and content managers. It helps applications, agents, and automated workflows turn that capability into repeatable tasks and useful downstream experiences.
Common use cases
- Build media monitoring, content intelligence, and publishing-support workflows.
- Create repeatable integrations that pass structured results to downstream business systems.
- Support scheduled jobs, internal tools, and agent workflows with structured results.