Unpacking Algorithmic News Engagement: How News Values Shape Audience Behaviors on Chinese TikTok (Douyin)

This study investigates the extent to which news values influence users’ news engagement processes in an algorithmically curated environment. We further distinguish the impacts of hard and soft news to better understand how news genre and characteristics interact in shaping audience behavior. Leveraging cloud-computing technology and web scraping, we collected and analyzed a total of 92,895 news-related videos from 2,663 verified news outlets on Douyin platform. Findings indicated that most of news factors proposed, i.e., prominent, unique, sentiment, and government’s agenda, appeared to be significantly associated with news engagement. We also present preliminary results showing that the impact of certain news factors is further amplified across hard and soft news genres. Our study contributes to understanding the mechanisms, characteristics, and conditions of news consumption in today’s media landscape. As people increasingly consume news through algorithm-driven platforms, this research has important implications for journalism, social media, and political communication studies.