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. Technological Framework Behind BitTruth

AI-powered Emotion Manipulation Detection

Natural Language Processing (NLP)

For Language Emotion Manipulation Detection, BitTruth employs advanced NLP algorithms, such as BERT (Bidirectional Encoder Representations from Transformers) and RoBERTa (A Robustly Optimized BERT Pretraining Approach). These models are trained to understand the contextual meaning of words and phrases in text, allowing BitTruth to detect subtle emotional cues and manipulation tactics such as urgency, fear, or exaggerated claims. The NLP models parse the language of advertisements, social media posts, and articles to identify emotional triggers and assess the level of emotional manipulation within the content.

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Last updated 2 months ago

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