BitTruth
  • 📖Executive Summary
  • ⏰Revolutionizing Trust in the Digital Age
    • Market Opportunity
    • Competitive Landscape
  • #️⃣BitTruth: Restoring Integrity in Digital Content through Emotion Analysis
    • Mission & Vision
  • 💼AI-Powered Language Emotion Manipulation Detection
    • Function Overview
    • Application Scenarios
    • Example
  • 😶AI-Powered Micro-Expression Detection
    • Function Overview
    • Application Scenarios
    • Example
  • How It Works
    • ☎️Language Emotion Manipulation Detection
    • 📡Micro-Expression Detection
  • Technological Framework Behind BitTruth
    • 🔋AI-powered Emotion Manipulation Detection
    • 🎙️Micro-Expression and Voice Tone Analysis
    • ⛓️Blockchain Integration for Decentralized Verification
    • 🧭API Integration for Businesses and Platforms
    • 🔐Unlocking the True Value of Digital Content
    • 💰Tokenomics
      • Utility of $BTT Tokens
      • Token Allocation
    • 🛣️Roadmap
    • ❓FAQ
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  1. AI-Powered Language Emotion Manipulation Detection

Example

Let’s consider an example of an advertisement text:

  • Ad Copy: “Only 3 days left for Double 11! Only 10 items left in stock!”

BitTruth’s AI would analyze this content and produce the following results:

  • Manipulation Index: 80%

  • Emotion Distribution:

40% Fear (The phrase “only 10 items left” creates a sense of scarcity and fear of missing out)

30% Excitement (The phrase “Only 3 days left” builds urgency and excitement)

  • Annotation: “‘Only 10 items left’ exaggerates scarcity”

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Last updated 2 months ago

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