Vaping Misinformation Detector (Beta)

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Separate myth from reality with our Vaping Misinformation Detector

Misconceptions on the relative safety of vaping to smoking stops smokers from making the life-changing decision to quit.

Recent surveys indicate that approximately 50% of smokers believe vaping is equally harmful as smoking. This knowledge gap creates significant barriers to harm reduction efforts and impacts consumer confidence in the sector.

Our Vaping Misinformation Detector provides vaping industry stakeholders with sophisticated content analysis tools to identify, counter, and contextualise misleading claims about vaping products and harm reduction.

How Our Solution Works

The Vaping Misinformation Detector employs advanced natural language processing to:

  • Analyse article content through a simple URL submission
  • Identify specific misinformation patterns using our finely-tuned model
  • Provide evidence-based counter-arguments from peer-reviewed research
  • Generate comprehensive reports suitable for professional use (coming soon!)

Professional Applications

  • Generate factual responses fast to misinformation affecting your market
  • Links to research in the results
  • Ensure marketing materials align with scientific consensus
  • Support responsible communication practices

Collaboration Opportunities

We welcome partnerships with research institutions, public health bodies, and industry stakeholders committed to evidence-based discourse. The platform can be customised to integrate with your existing digital infrastructure or deployed as a standalone solution.

Try the detector

Try it out – explore how the Vaping Misinformation Detector can help your organisation.

Current Beta Status

Important Notice: The Vaping Misinformation Detector is currently in Beta phase as we continue to refine our algorithms and incorporate client feedback. During this developmental stage, users should be aware of certain limitations:

  • The system may occasionally generate false positives, identifying statements as misinformation that require additional context
  • Detection accuracy varies depending on the complexity and framing of claims
  • The knowledge base is being continuously expanded with new research
  • Processing times may vary depending on article length and complexity

We’re actively collecting user feedback to address these limitations and enhance the tool’s precision and reliability. Your participation during this Beta phase directly contributes to strengthening the system’s capabilities