Clickbait vs. quality: How engagement-based optimization shapes the content landscape in online platforms
Online content platforms commonly use engagement-based optimization when making
recommendations. This encourages content creators to invest in quality, but also rewards …
recommendations. This encourages content creators to invest in quality, but also rewards …
Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms
On User-Generated Content (UGC) platforms, recommendation algorithms significantly
impact creators' motivation to produce content as they compete for algorithmically allocated …
impact creators' motivation to produce content as they compete for algorithmically allocated …
PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators
We introduce the Proportional Payoff Allocation Game (PPA-Game) to model how agents,
akin to content creators on platforms like YouTube and TikTok, compete for divisible …
akin to content creators on platforms like YouTube and TikTok, compete for divisible …
User Welfare Optimization in Recommender Systems with Competing Content Creators
Driven by the new economic opportunities created by the creator economy, an increasing
number of content creators rely on and compete for revenue generated from online content …
number of content creators rely on and compete for revenue generated from online content …
User-Creator Feature Polarization in Recommender Systems with Dual Influence
Recommender systems serve the dual purpose of presenting relevant content to users and
helping content creators reach their target audience. The dual nature of these systems …
helping content creators reach their target audience. The dual nature of these systems …