Impacts of Reducing Visibility of Friends’ Liked Content on User Content Engagement Across Newsfeed Channels

Nowadays, online platforms constantly adjust their newsfeeds to boost engagement, often emphasizing nonsocial channels such as algorithmic recommendations over social ones such as user networks. However, ignoring the interactions between these channels can have unintended consequences. This study delves into this by assessing the impacts of a policy change that reduced the visibility of friends’ liked content on a major discussion platform. We found this led to an overall decrease in users’ content engagement. Although users engaged more with their friends’ original posts and trending topics, their interaction with nonsocial content such as algorithmic recommendations decreased. This reveals a key insight: social channels act as substitutes for one another but are complementary to nonsocial, algorithmic channels. Vibrant social activity is crucial for driving traffic to other parts of a platform. Crucially, the change also made users’ content engagement less diverse. Friends’ liked content is a key source of exposure to niche topics. For platform operators, this means that sidelining social features in favor of algorithmic feeds can backfire, reducing overall engagement and diversity. For policymakers concerned about online echo chambers, our findings suggest that content shared through extended social networks is vital for promoting a wider range of content.

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Publication Details

Journal
Information Systems Research
Published
2025-08-20
DOI
https://doi.org/10.1287/isre.2024.0871
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00
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article

Impacts of Reducing Visibility of Friends’ Liked Content on User Content Engagement Across Newsfeed Channels

Zhongju Zhang, Xiaohui Zhang, Qinglai He
1 links
Information Systems Research
Digital Marketing and Social Media
article

Impacts of Reducing Visibility of Friends’ Liked Content on User Content Engagement Across Newsfeed Channels

Zhongju Zhang, Xiaohui Zhang, Qinglai He
article en

Abstract

Nowadays, online platforms constantly adjust their newsfeeds to boost engagement, often emphasizing nonsocial channels such as algorithmic recommendations over social ones such as user networks. However, ignoring the interactions between these channels can have unintended consequences. This study delves into this by assessing the impacts of a policy change that reduced the visibility of friends’ liked content on a major discussion platform. We found this led to an overall decrease in users’ content engagement. Although users engaged more with their friends’ original posts and trending topics, their interaction with nonsocial content such as algorithmic recommendations decreased. This reveals a key insight: social channels act as substitutes for one another but are complementary to nonsocial, algorithmic channels. Vibrant social activity is crucial for driving traffic to other parts of a platform. Crucially, the change also made users’ content engagement less diverse. Friends’ liked content is a key source of exposure to niche topics. For platform operators, this means that sidelining social features in favor of algorithmic feeds can backfire, reducing overall engagement and diversity. For policymakers concerned about online echo chambers, our findings suggest that content shared through extended social networks is vital for promoting a wider range of content.

Information Systems Research
University of Wisconsin–Madison (US), University of Wisconsin–Milwaukee (US), Arizona State University (US)
Openalex Percentile: Top 71%
Digital Marketing and Social Media
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Impacts of Reducing Visibility of Friends’ Liked Content on User Content Engagement Across Newsfeed Channels — Zhongju Zhang, Xiaohui Zhang, et al. · Information Systems Research (2025) | TGRS Research Map | TGRS