tiktok/analytics/detect-fake-views

Detect fake views in video

Purpose:

• 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

Parameters:

• item_id: Video ID, required parameter, can be extracted from video URL (e.g., 7460937381265411370 from https://www.tiktok.com/@tiktok/video/7460937381265411370)
• content_category: Content category, optional parameter, affects engagement rate benchmarks, options include:
  • default: Default category for general content
  • entertainment: Entertainment content, expected to have higher engagement
  • education: Educational content, expected to have moderate engagement and higher save rates
  • product: Product content, expected to have lower engagement but higher conversion
  • verified_large: Large verified accounts, expected to have appropriately lower engagement rates

Return Description:

• video_metrics: Core video metrics

  • total_views: Total number of views
  • total_likes: Total number of likes
  • total_comments: Total number of comments
  • total_favorites: Total number of saves
  • total_shares: Total number of shares
  • engagement_rates: Engagement rate metrics, higher is better
    • like_ratio: Like rate, normal range 1-10%, may be lower for large accounts
    • comment_ratio: Comment rate, normal range 0.1-0.5%, excellent if above 1%
    • favorite_ratio: Save rate, normal range 0.05-0.8%
    • share_ratio: Share rate, normal range 0.05-0.5%, excellent if above 1%

• creator_metrics: Creator account health indicators

  • account_age_days: Account age in days, longer is more credible
  • follower_count: Number of followers, affects expected view count
  • verified: Whether account is verified, verified accounts have higher credibility
  • trust_score: Account trust score (0-100), higher is more trustworthy

• content_metrics: Content quality indicators

  • content_type: Content type (video, image, etc.)
  • created_by_ai: Whether AI-generated, AI-generated content may have specific traffic patterns
  • high_quality_upload: Whether high-quality upload, high-quality uploads are more credible

• fake_view_analysis: Comprehensive fake traffic analysis

  • fake_score: Fake view score (0-100), lower is better:
    • 0-20: Very low risk, natural traffic patterns
    • 20-40: Low risk, may have minor anomalies but not problematic
    • 40-60: Medium risk, anomalies worth attention
    • 60-80: High risk, obvious fake traffic characteristics
    • 80-100: Very high risk, almost certainly fake traffic
  • confidence_level: Risk level, categorized as "Minimal", "Low", "Medium", "High"
  • estimated_fake_views: Estimated fake views, calculated based on fake traffic model
  • fake_view_percentage: Fake view percentage, proportion of fake views to total views
  • is_suspicious: Whether suspicious, comprehensive judgment if attention is needed
  • main_detection_reason: Main detection reason, most significant anomaly feature
  • component_scores: Dimensional anomaly scores, each 0-100, lower is better:
    • engagement_score: Engagement anomaly score
    • distribution_score: Distribution anomaly score
    • consistency_score: Consistency anomaly score
    • creator_credibility_score: Creator credibility anomaly score
    • content_authenticity_score: Content authenticity anomaly score
    • follower_correlation_score: Follower correlation anomaly score
    • racing_mechanism_score: Racing mechanism anomaly score
    • fan_growth_score: Fan growth anomaly score

• traffic_pool: Traffic pool analysis (TikTok racing mechanism)

  • current_tier: Current traffic pool level (1-8), higher means more traffic
  • current_tier_name: Current traffic pool name
  • expected_tier: Expected traffic pool level, based on organic traffic prediction
  • expected_tier_name: Expected traffic pool name
  • current_views_range: Current traffic pool expected view range
  • expected_views_range: Expected traffic pool view range
  • estimated_organic_views: Estimated organic views, real views after deducting fake ones

• suspicious_features: List of suspicious features, specific detected anomalies

• recommendations: Recommended actions

  • action: Recommended action type, possible values include:
    • no_action: No action needed, healthy content
    • monitor: Continuous monitoring, minor anomalies present
    • scheduled_review: Schedule review, anomalies worth attention
    • immediate_review: Immediate review, serious anomalies present
  • risk_level: Risk level ("low", "medium", "high", "critical")
  • potential_revenue_impact: Potential revenue impact
  • suggested_steps: Suggested steps, specific action recommendations

• mcn_report: (Optional) MCN business impact analysis report, applicable for business accounts

  • summary: Summary information
  • business_impact: Business impact assessment
    • revenue_impact: Revenue impact assessment
    • brand_safety_impact: Brand safety impact
    • platform_relationship: Platform relationship impact
    • contract_impact: Contract impact assessment
  • recommended_actions: Recommended action list
  • historical_context: Historical background data

Features and Advantages:

• Precise evaluation system built on TikTok's native Traffic Pool theory
• Comprehensive analysis across 8 dimensions and 20+ metrics, covering traffic, engagement, creator, content, etc.
• Adaptive algorithm automatically adjusts thresholds based on account size, verification status, content type
• Anomaly detection based on big data statistical models, accurately identifies unnatural traffic patterns
• Provides customized evaluation standards for different account sizes (micro, small, medium, large, extra-large)
• Delivers detailed business impact analysis and specific, actionable recommendations

Example Response:

{
  "code": 200,
  "router": "/api/v1/tiktok/analytics/detect_fake_views",
  "params": {
    "item_id": "7460937381265411370",
    "content_category": "verified_large"
  },
  "data": {
    "video_metrics": {
      "total_views": 159414915,
      "total_likes": 15817234,
      "total_comments": 392493,
      "total_favorites": 1051470,
      "total_shares": 1312741,
      "engagement_rates": {
        "like_ratio": 0.09922,
        "comment_ratio": 0.00246,
        "favorite_ratio": 0.0066,
        "share_ratio": 0.00823
      }
    },
    "creator_metrics": {
      "account_age_days": 3733.94,
      "follower_count": 89827771,
      "verified": true,
      "trust_score": 100
    },
    "content_metrics": {
      "content_type": "video",
      "created_by_ai": false,
      "high_quality_upload": true
    },
    "fake_view_analysis": {
      "fake_score": 7.16,
      "confidence_level": "Minimal",
      "estimated_fake_views": 7970745,
      "fake_view_percentage": 5.0,
      "is_suspicious": false,
      "main_detection_reason": "Statistical View Anomalies",
      "component_scores": {
        "engagement_score": 0.0,
        "distribution_score": 10.0,
        "consistency_score": 0,
        "creator_credibility_score": 0,
        "content_authenticity_score": 34.0,
        "follower_correlation_score": 35.0,
        "racing_mechanism_score": 0,
        "fan_growth_score": 45
      }
    },
    "traffic_pool": {
      "current_tier": 8,
      "current_tier_name": "8th-Level Traffic Pool",
      "expected_tier": 8,
      "expected_tier_name": "8th-Level Traffic Pool",
      "current_views_range": "30M+",
      "expected_views_range": "30M+",
      "estimated_organic_views": 148000807
    },
    "suspicious_features": [
      "Suspicious: Reached 100000 followers from 10000 in only 31 days",
      "Suspicious: Account gaining 24063 followers per day on average"
    ],
    "recommendations": {
      "action": "no_action",
      "risk_level": "low",
      "potential_revenue_impact": "minimal",
      "suggested_steps": [
        "No immediate action required",
        "Include in routine monitoring"
      ]
    },
    "mcn_report": {
      "summary": {
        "estimated_revenue_impact": 7970.745,
        "recommended_actions": "No immediate action required"
      },
      "business_impact": {
        "revenue_impact": {
          "level": "low",
          "estimated_amount": 7970.745
        },
        "brand_safety_impact": {
          "level": "minimal"
        },
        "platform_relationship": {
          "status": "good"
        }
      }
    }
  }
}

Imported from a validated TikHub OpenAPI document. Pricing must be reviewed before enabling.