The Impact of Recommendation Algorithms Embedded in Artificial Intelligence Tools of Social Media on the Media Preferences of Youth: A Field Study

Abstract

Social media platforms rely on “recommendation algorithms” embedded within artificial intelligence tools to organize and direct content toward users, even shaping audience priorities in continuing to follow specific types of media production—whether news, entertainment, or otherwise. As a result, these algorithms contribute to reshaping the media preferences of target groups, especially youth, given their numerical dominance and active engagement.

This study aims to analyze the impact of these algorithms on patterns of media content preference among young people, in terms of content type (political, entertainment, sexual, economic, religious, etc.), their level of engagement with it, and their awareness of how these systems operate—systems that represent the most visible and prominent aspects of algorithmic influence.

The study employs a descriptive methodology and is conducted using a questionnaire as the data collection tool. The fieldwork involves a sample of 100 active young users of social media.,

The study seeks to reveal the extent to which recommendation algorithms influence media desires and contribute to the formation of narrow spheres of interest, potentially reinforcing the reproduction of informational bubbles This is what was clearly evident from the results