Featured Project

SeenOnScreen

As a media researcher and social psychologist, I noticed that the media representation space was dominated almost exclusively by top-down, expert-driven analyses. While these expert perspectives are valuable, they miss something critical: the lived experiences of people with those identities, especially young people and multiply-marginalized communities who are often excluded from positions of expertise.

With this in mind, I built SeenOnScreen: a platform where anyone can rate media based on how well it represents their identity and experiences, and discover new content that might make them feel seen.

Visit Gated Site

Project Status

Gated Beta

Launch Date

June 2025

The Problem & The Solution

The Problem

Media representation analysis has been dominated by expert-driven commentary, missing diverse perspectives from people with lived experiences of marginalized identities.

Marginalized communities—especially multiply-marginalized people and young people—have fewer opportunities to occupy positions of expertise, yet their perspectives are essential for authentic representation.

The entertainment industry lacks comprehensive, identity-based feedback from actual audiences about representation quality.

The Solution

SeenOnScreen democratizes media representation feedback by allowing anyone to rate content based on their personal experiences and identity.

Users rate content on multiple dimensions: how much they like it, how much they see themselves reflected, how well it captures their cultural identity and specific experiences.

The platform aggregates this data to provide both personalized recommendations and public consensus feedback for the media industry on representation quality.

Key Features

Powerful tools for discovery and authentic feedback on representation

Multi-Dimensional Rating System

Rate content on enjoyment, personal reflection, cultural accuracy, and how well it captures your specific experiences—creating nuanced feedback beyond simple ratings.

Identity-Filtered Recommendations

Discover media that users with similar identities love. Search any title and see aggregated ratings filtered by specific user identities.

Comprehensive Content Library

Browse thousands of titles across television shows, movies, video games, and YouTube content creators—all in one place.

Community-Driven Insights

Connect with others who share your experiences. See what your community is watching and how they're rating representation quality.

Industry Feedback Loop

Generate public consensus data that entertainment industry professionals can use to understand how well their content represents diverse identities.

Personalized Discovery

Find content you might love but wouldn't have discovered otherwise—media that will make you feel seen, created by people who understand your experience.

The Impact

Centering marginalized voices to improve media representation

For Audiences

Discover content that resonates with your identity and experiences. Find representation that builds confidence, creates belonging, and makes you feel truly seen.

For Content Creators

Access authentic feedback from diverse audiences about representation quality. Understand how your content is experienced by people with the identities you're representing.

For Marginalized Communities

Amplify voices that are often excluded from expert positions. Ensure multiply-marginalized perspectives—especially from young people—shape the conversation about representation.

For the Entertainment Industry

Move beyond expert-only analysis to incorporate broad, authentic audience perspectives. Make data-driven decisions about representation that reflect actual audience experiences.

Building SeenOnScreen

Leveraging AI and modern web technologies for scalable impact

I built SeenOnScreen as an independent project with the assistance of Claude 3.5 and 3.7 Sonnet as AI coding assistants. The platform is designed to scale, enabling collection and analysis of representation data across thousands of media titles.

The web application combines a comprehensive media database with sophisticated rating mechanisms and identity-based filtering, all designed to center user experiences and provide meaningful insights.

AI-Assisted Development

Claude 3.5 & 3.7 Sonnet

Web Application

Rating System Design

Identity-Based Filtering

Data Aggregation

Community Features

Interested in Learning More?

SeenOnScreen is currently in gated beta. Reach out to learn more about the platform, discuss partnership opportunities, or explore how this approach to representation feedback could benefit your organization.

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