Unpacking Algorithmic News Engagement

How News Values Shape Audience Behaviors on Chinese TikTok (Douyin)

Bibliographic Data

ID7162292
AuthorsJinhui Li (0000-0002-9823-8038, Jinan University), Wen Shi (0000-0003-1022-6639, Jinan University, corresponding author)
Year2025
Volume26
Issue9
Pages1092-1107
Publication date2025-07-04
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournalism Studies (JOURNAL)
Journal identifiersISSN: 1461-670X • E-ISSN: 1469-9699
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/1461670x.2025.2489585
OpenAlexW4409232613
LanguageEN
Citations received2
References cited57

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

Advertising · Business · Linguistics · Media studies · News media · News values · Political science · Sociology · Unpacking · Computer Science · Impact of Technology on Adolescents · Media Studies and Communication · Social Media and Politics

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