Journal Article

Impact of YouTube User‐Generated Content on News Dissemination and Youth Information Reception

Yingqi, Liu, Shan, Jiang, Jianhong, Sun, Chunqiong, Wu

2025

Overview

Background User‐generated content (UGC) on YouTube has reshaped news dissemination, fostered engagement, raised concerns about credibility, algorithmic influence and the spread of misinformation. This study addresses the gap in understanding how UGC engagement, trust and algorithmic awareness influence digital news consumption. Methods A convergent parallel mixed‐methods design was employed, integrating survey data (n = 100), qualitative interviews and content analysis of 200 YouTube news videos. Data were collected over 6 weeks. Quantitative analyses included ANOVA, multivariate regression and structural equation modelling (SEM), while qualitative data were thematically analysed to contextualise statistical findings. Results UGC news consumption (M = 3.21, SD = 1.14) exceeded traditional news (M = 2.95, SD = 1.20), with trust in UGC (M = 3.48, SD = 1.05) surpassing traditional sources (M = 3.12, SD = 1.17). SEM analysis confirmed that UGC engagement significantly increased trust (β = 0.42, p < 0.001), while algorithmic influence negatively affected trust (β = −0.33, p = 0.015). Sensationalist content attracted higher engagement (30.0%) but had lower credibility, with misinformation prevalent in 38.0% of analysed videos. Conclusion Findings highlight the need for platform transparency, stronger content verification and policy interventions to balance engagement‐driven algorithms and news credibility. Media literacy initiatives are crucial for equipping users with the critical evaluation skills they need.

• Publisher: John Wiley & Sons, Inc,Wiley
• Subject: Adolescent / Adult / algorithmic influence / Algorithms / Communication / Consumption / Content analysis / Content creation / Credibility / Data / Dependency theory / digital engagement / Dissemination / Ethics / False information / Female / Focus groups / Humans / Influence / Information dissemination / Information Dissemination - methods / Internet / Interviews as Topic / Journalism / Literacy / Male / Mass media / Media literacy / Misinformation / News / News media / Original / Participation / Qualitative analysis / Qualitative Research / Quantitative analysis / Social Media / Social networks / Statistical analysis / Structural equation modeling / Surveys and Questionnaires / Transparency / Trust / trust in media / User generated content / Variance analysis / Verification / Video / Young Adult / Young adults / YouTube news