# Yourfeed: Towards open science and interoperable systems for social media

arXiv: https://arxiv.org/abs/2207.07478 · HTML: https://mlsanity.com/paper/2207.07478/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Jul 2022.

## Built on by (most cited first, 1 of 1)

- ["Impressively Scary:" Exploring User Perceptions and Reactions to Unraveling Machine Learning Models in Social Media Applications](https://mlsanity.com/paper/2503.03927/) (2025)

## Abstract (arXiv)

Existing social media platforms (SMPs) make it incredibly difficult for researchers to conduct studies on social media, which in turn has created a knowledge gap between academia and industry about the effects of platform design on user behavior. To close the gap, we introduce Yourfeed, a research tool for conducting ecologically valid social media research. We introduce the platform architecture, as well key opportunities such as assessing the effects of exposure of content on downstream beliefs and attitudes, measuring attentional exposure via dwell time, and evaluating heterogeneous newsfeed algorithms. We discuss the underlying philosophy of interoperability for social media and future developments for the platform.