Exploring Users' Experiences of "Suggested Posts" in Social Media Through the Lens of Social Networking and Interactions

Abstract

Many social media feeds are incorporated with “Suggested Posts,” an AI-infused feature that recommends algorithmically selected posts from accounts that a user does not follow. While such recommendations might increase user engagement with the platforms, there lacks understanding on how such system-driven recommendations influence the primary purpose of social media use: social interactions. We conducted semi-structured interviews with 12 Instagram users to investigate how they perceive the “Suggested Posts” feature in relation to their in-app social interaction practices. Our findings reveal that suggested posts acted as a double-edged sword for communication with their actual friends, acted as an obstacle for digital self-presentation, and acted as an unwanted force that compel users to increase social groups. Based on the findings, we discuss the importance of considering user agency over social interactions in designing user experiences of recommendations provided in social media.