The impact of source-based aggregation on content consumption behaviors

As content delivery increasingly shifts to digital platforms, users face significant challenges of information overload and misinformation. An emerging interface-level presentation strategy to address these issues is Source-Based Aggregation (SBA), where multiple posts from the same source are grouped into a collapsed display format. SBA has been widely adopted on platforms like Facebook and WeChat Moments, yet its behavioral consequences and underlying mechanisms remain underexplored. By design, SBA enhances perceived credibility by increasing source salience, but it simultaneously reduces perceived diversity, creating a behavioral trade-off. This study investigates how SBA influences content consumption by incorporating information foraging theory, source salience, and diversity-seeking preferences into a unified theoretical framework. We also conceptualize content consumption as a two-stage process: content selection (whether a user clicks through to view full content) and content engagement (how deeply users interact with the content once selected). To empirically test these effects, we exploit a real-world quasi-experiment using individual-level clickstream data from a major news outlet. Leveraging a difference-in-differences (DID) approach, we examine the effects of SBA on user content consumption behaviors. Results show that SBA decreases content selection but increases subsequent engagement. Post-hoc analyses further reveal that SBA effects are more positive among users with stronger ties to the content source. This study contributes to research on aggregated information presentation and digital content consumption by revealing how interface-level aggregation strategies affect user behaviors. Practically, we offer actionable insights for stakeholders seeking to balance source credibility and diversity to boost user engagement and content effectiveness.