Uncovering the Interaction Equation: Quantifying the Effect of User Interactions on Social Media Homepage Recommendations

TL;DR

This study investigates how user interactions affect homepage content curation on YouTube, Reddit, and X, revealing platform-specific behaviors and topic deprioritization through carefully designed experiments.

Contribution

It provides a detailed analysis of the influence of user interactions on social media homepage recommendations across multiple platforms, highlighting differences and common patterns.

Findings

User interactions significantly influence homepage content selection.

Algorithms respond differently across platforms to user behaviors.

Evidence of deprioritization of certain topics based on interactions.

Abstract

Social media platforms depend on algorithms to select, curate, and deliver content personalized for their users. These algorithms leverage users' past interactions and extensive content libraries to retrieve and rank content that personalizes experiences and boosts engagement. Among various modalities through which this algorithmically curated content may be delivered, the homepage feed is the most prominent. This paper presents a comprehensive study of how prior user interactions influence the content presented on users' homepage feeds across three major platforms: YouTube, Reddit, and X (formerly Twitter). We use a series of carefully designed experiments to gather data capable of uncovering the influence of specific user interactions on homepage content. This study provides insights into the behaviors of the content curation algorithms used by each platform, how they respond to user interactions, and also uncovers evidence of deprioritization of specific topics.