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| {% extends "base.html" %} | |
| {% block title %}Home - Detect Fake News{% endblock %} | |
| {% block content %} | |
| <section class="home-hero-section"> | |
| <div class="container home-content-wrapper"> | |
| <div class="row align-items-center"> | |
| <div class="col-lg-6 home-text-area"> | |
| <h1 class="home-title"> | |
| Detect Fake News with Confidence | |
| <!-- <span class="fake-news-highlight">Fake News</span> with Confidence --> | |
| </h1> | |
| <p class="home-subtitle"> | |
| Our AI-powered platform helps you identify misinformation and verify the authenticity of news articles and information online. | |
| </p> | |
| <div class="d-flex gap-3"> | |
| <a href="{{ url_for('index') }}" class="btn btn-primary btn-lg" style="background-color: dodgerblue; border-color:dodgerblue"> | |
| <!-- "background-color: #4f46e5; border-color: #4f46e5;" --> | |
| Verify News Now</a> | |
| <a href="{{ url_for('about') }}" class="btn btn-outline-secondary btn-lg" style="border-color: #dee2e6; color: #343a40; background-color: #dee2e6;">Learn More</a> | |
| </div> | |
| </div> | |
| <div class="col-lg-6 d-flex justify-content-center justify-content-lg-end mt-5 mt-lg-0"> | |
| <div class="home-image-box"> | |
| <img src="https://www.keele.ac.uk/research/researchnews/2025/january/artificial-intelligence/fake-news-detector-960.jpg" alt="AI Powered Platform Graphic" style="max-width: 450px;"> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </section> | |
| <div class="app-box-2"> | |
| <div class="container mt-5 mb-5"> | |
| <h4 class="text-center mb-5 home-title" style="color:dodgerblue;">How TruthCheck Works: The AI Verification Process</h4> | |
| <div class="row" > | |
| <div class="col-lg-4 mb-4"> | |
| <div class="card shadow-sm h-100"> | |
| <div class="card-body"> | |
| <h5 class="card-title fw-bold">1. Text Embedding (Vectorization)</h5> | |
| <p class="card-text"> | |
| The core of our technology is the AI model, "all-MiniLM-L6-v2". | |
| It converts the news headline you enter into a "numerical vector" (embedding). This vector mathematically represents the semantic meaning of the text, allowing for objective comparison. | |
| </p> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="col-lg-4 mb-4"> | |
| <div class="card shadow-sm h-100"> | |
| <div class="card-body"> | |
| <h5 class="card-title fw-bold">2. Data Sourcing & Comparison</h5> | |
| <p class="card-text"> | |
| The detector first checks for an extremely high match (similarity > 0.9) against a database of "pre-verified facts". | |
| If no direct match is found, it queries the web using the <b>SerpAPI</b> (Google Search API) to retrieve the top 5 most relevant articles from trusted online sources in real-time. | |
| </p> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="col-lg-4 mb-4"> | |
| <div class="card shadow-sm h-100"> | |
| <div class="card-body"> | |
| <h5 class="card-title fw-bold">3. Verdict Generation</h5> | |
| <p class="card-text"> | |
| Beyond just similarity, our AI uses a <b>Cross-Encoder</b> to check for logical contradictions. | |
| Even if words match, if the meaning is opposite (like 'Won' vs 'Lost'), the <b>T5 Model</b> identifies the error and provides a detailed explanation. | |
| </p> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="app-box-2"> | |
| <h3 class="mt-5 mb-5 text-center home-title" style="color:dodgerblue">Technology Summary</h3> | |
| <ul class="list-group list-group-flush mx-auto" style="max-width: 800px;"> | |
| <li class="list-group-item"><b>Core NLP Model:</b> all-MiniLM-L6-v2 Sentence Transformer</li> | |
| <li class="list-group-item"><b>Real-time Data:</b> Google Search results via serpapi</li> | |
| <li class="list-group-item"><b>Backend Framework:</b> Flask (Python)</li> | |
| <li class="list-group-item"><b>Success Threshold:</b> Semantic similarity score of *0.7*</li> | |
| </ul> | |
| </div> | |
| {% endblock %} |