能见度
内容(测量理论)
用户生成的内容
计算机科学
频道(广播)
用户参与度
互联网隐私
万维网
多媒体
社会化媒体
计算机网络
光学
数学分析
物理
数学
作者
Xiaohui Zhang,Qinglai He,Zhongju Zhang
标识
DOI:10.1287/isre.2024.0871
摘要
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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