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Chirp

Personalized, transparent, and user-controlled content curation

Inspiration

When Instagram’s algorithm glitched and showed disturbing content across feeds for hours, it exposed a big issue: users have no real control over what recommendation systems decide to show them. I wanted to reimagine how social media feeds could work if people could actually define what they wanted to see and understand why it was recommended.

What It Does

This project curates a personalized Twitter (X) feed based on user-selected themes like Productivity, Work-Life Balance, or Memes. Instead of relying on opaque engagement metrics, it analyzes tweets based on their meaning and tone to decide which ones best fit a user’s chosen theme.

Each tweet includes a short explanation of why it was selected so users can see exactly how their feed is being shaped.

How I Built It

X API → tweets.json → Gemini AI Scoring → scored_tweets.json → React Feed

Data Collection: Pulled 100 recent tweets with images using the X API.
Analysis & Scoring: Processed tweet text and metadata through Gemini to assign a semantic relevance score (0–10) for each theme.
Filtering: Kept only the top-scoring tweets for display.
Frontend: Built a clean React interface that displays tweets, scores, and AI reasoning.

Challenges

Working solo meant handling both the backend scoring pipeline and frontend design. Integrating the X API and structuring the data for AI scoring took some time, and balancing clarity with transparency in the UI was an interesting design problem.

What Makes It Stand Out

User-defined feeds: You pick what kind of content you want.
Explainable recommendations: Each tweet includes a reasoning summary.
Safer content filtering: Minimizes unwanted or harmful material.
Transparent design: Users see how their feed is built, not just the results.

Impact

This project shows how recommendation systems can be made safer and more transparent without losing personalization. By giving control back to the user, it encourages more intentional and trustworthy social media experiences.