HOW_TO_TEST_ACCURACY.md

🧪 HOW TO RUN ACCURACY TEST

Quick Test Instructions

Step 1: Start the Server

Open a PowerShell terminal and run:

cd D:\mis_2\LinkScout
python combined_server.py

Wait until you see:

✅ Core models loaded (RoBERTa, Emotion, NER, Hate, Clickbait, Bias)
🤖 [RL] Reinforcement Learning Agent initialized
  RL Agent: READY (Episodes: 0)
  Server starting...

Step 2: Run the Test (in a NEW terminal)

Open a NEW PowerShell window and run:

cd D:\mis_2\LinkScout
python test_simple_manual.py

Press ENTER when prompted.

Step 3: Review Results

The test will process 10 samples:

• 5 Fake News (COVID conspiracies, election fraud, chemtrails, 5G, cancer cures)
• 5 Real News (WHO, NASA, MIT, CDC, Federal Reserve)

You'll see:

• ✅ Accuracy (target: 70%+)
• ✅ False Positive Rate (target: <20%)
• ✅ Recall (target: 60%+)
• ✅ Precision (target: 60%+)

Results saved to: simple_test_results.json

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What the Test Validates

✅ Database Expansion (97 false claims)

The test includes content matching claims from our expanded database:

• COVID vaccine misinformation
• Election fraud claims
• Chemtrails conspiracy
• 5G health concerns
• Alternative medicine claims

✅ ML Model Integration (35% weight)

RoBERTa fake news classifier analyzes all samples and contributes 35% to risk score.

✅ Revolutionary Detection (40% weight)

8-phase linguistic analysis detects propaganda, emotional manipulation, etc.

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Expected Results

Based on our improvements:

Before Improvements:

• Accuracy: ~48%
• Many false claims missed
• ML model not used

After Improvements (Target):

• Accuracy: 70-80% ✅
• False Positive Rate: <20% ✅
• Recall: 60-80% ✅
• Database + ML working together

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Sample Output

🔍 Testing Sample #1: COVID vaccine conspiracy theories
   Expected: FAKE
   Content: COVID-19 vaccines contain microchips...
   ✅ Risk Score: 78.5%
   ✅ CORRECT - Detected as high risk

🔍 Testing Sample #6: Credible science reporting
   Expected: REAL
   Content: According to peer-reviewed study in Nature...
   ✅ Risk Score: 18.2%
   ✅ CORRECT - Detected as low risk

📈 FINAL RESULTS
================================================================================
📊 Confusion Matrix:
   True Positives (TP):  4 - Fake news correctly detected
   True Negatives (TN):  4 - Real news correctly identified
   False Positives (FP): 1 - Real news marked as fake
   False Negatives (FN): 1 - Fake news missed

🎯 Key Metrics:
   Accuracy:  80.0%  ✅
   FP Rate:   20.0%  ✅
   Recall:    80.0%  ✅
   Precision: 80.0%  ✅

✅ EXCELLENT - System performing well!

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Troubleshooting

Server won't start:

# Make sure you're in the right directory
cd D:\mis_2\LinkScout
ls combined_server.py  # Should exist

# Try running directly
python combined_server.py

Test says "Connection refused":

• Server not running yet
• Wait 30 seconds after starting server
• Check server terminal shows "Server starting..."

All tests fail:

• Check server didn't crash (look at server terminal)
• Server might be overloaded - restart it
• Try running test again

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Alternative: Manual Testing

If automated test has issues, test manually:

1. Start server: python combined_server.py
2. Open Chrome extension
3. Visit these sites:
   • Fake: conspiracy theory sites, health misinformation
   • Real: BBC, Reuters, Nature, WHO official pages
4. Click "Scan Page" and check risk scores
5. Fake news should show 60-100% risk
6. Real news should show 0-40% risk

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The test will show if our 3 implementations (Database + ML + Test Suite) improved accuracy from 48% to 70-80%! 🎯