Trust-O-Meter

A tiny review app where users give anonymous ratings (1–5 stars) for a club/event, and each rating is stored on the Algorand blockchain for immutability.

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🚦 Trust-O-Meter

📌 About the Project

Trust-O-Meter is a responsive, interactive web application designed to analyze and visualize user-generated ratings data in a way that reveals trustworthiness scores. The project is aimed at promoting transparency and credibility in user-review ecosystems: such as marketplaces, freelancer platforms, and collaborative communities, where trust is key.

🌟 Inspiration

The inspiration for Trust-O-Meter came from observing how unreliable or manipulated online reviews can damage genuine interactions and business reputations. Whether it’s fake reviews, biased ratings, or bad actors trying to game the system, there's a clear need for a smarter way to filter trustworthy input from noise. This project was born out of the idea to leverage simple algorithms and user behaviors to create a score that reflects credibility, not just popularity.

🧠 What We Learned

Building the Trust-O-Meter taught us valuable lessons across both front-end and back-end development:

  • UI/UX design: Keeping the interface clean and intuitive helped us appreciate user-centric design.
  • React fundamentals: We deepened our understanding of state management, component-based architecture, and hooks.
  • Backend integration: Connecting to a real backend taught us how to properly handle asynchronous data and error handling.
  • Working with types: We learned how to enforce consistent data through TypeScript and custom types.
  • Exporting and searching data: We implemented functions to dynamically search and export data in JSON format.

🔧 How We Built It

The Trust-O-Meter is a full-stack project using the following tools and technologies:

  • Frontend:
    • React with TypeScript
    • Tailwind CSS for styling
    • Lucide Icons for modern UI elements
    • Custom components like buttons, toggles, and search bars

  • Backend:
    • Node.js server (simulated or stubbed in the current version)
    • Custom utility files for logic:
    • functionality.ts (handles export logic)
    • algorand.ts (contains search/filter algorithms)

  • Data Management:
    • Ratings are stored as RatingData objects with key metrics for visualization
    • Exporting logic enables easy CSV or JSON download for further analysis

  • Features:
    • Light/dark mode toggle
    • Real-time search/filtering of ratings
    • Export functionality
    • Clean and intuitive settings interface

🧩 Challenges Faced

Building the Trust-O-Meter came with a few challenges:

  1. Dynamic UI logic – Ensuring the page re-rendered efficiently with updated data while keeping components clean and maintainable.
  2. Modularizing code – Creating and importing utility functions across multiple files took trial-and-error, especially with TypeScript types and imports.
  3. Exporting Data – Building a consistent export function for both JSON and CSV that respected user input and formatting was tricky.
  4. Search Accuracy – Implementing search that could handle fuzzy matches and still be performant with potentially large datasets.

✅ Final Thoughts

Trust-O-Meter was more than just a technical project, it was a practical exploration of how software can build accountability and foster trust. It pushed us to balance clean code with clean design, and reminded us that a tool is only as good as its ability to empower the people who use it.

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