Inspiration

Online users are increasingly exposed to deceptive advertisements and dark patterns. We wanted to create an AI-powered tool that helps users evaluate the credibility of online content instead of simply blocking ads.

What it does

C2LIA is a Chrome extension connected to a Spring Boot API that analyzes:

• Web pages for dark patterns
• Text for misleading claims
• Videos for deceptive visual content
• Audio for manipulative speech

It combines the results into a single credibility score with detailed explanations.

How we built it

• Chrome Extension (Frontend)
• Spring Boot REST API (Backend)
• AI/NLP models for text analysis
• Multimedia processing for video and audio
• Scoring engine combining all analysis modules

Challenges we ran into

• Processing multiple content types (text, video, audio, web)
• Designing a unified credibility score
• Optimizing API response time
• Working within hackathon deadlines

Accomplishments that we're proud of

• Built a working end-to-end prototype
• Integrated four AI analysis modules
• Developed a modular architecture
• Created a simple and intuitive user experience

What we learned

• Browser extension development
• Spring Boot API integration
• AI and NLP integration
• Multimedia processing
• Team collaboration under time constraints

What's next for C2LIA

• Real-time analysis
• Better AI models
• Support for Firefox and Edge
• Multilingual support
• Community feedback system
• Larger datasets to improve accuracy

Built With

• css
• docker
• ffmpeg
• html
• java
• javascript
• json
• maven
• rest
• springboot