Bandung, November 2026 — Researchers from the Research Center for Information and Communication Technology (PPTIK), Institut Teknologi Bandung (ITB), have published a study in the International Journal on Informatics Visualization (JOIV), titled “A Hybrid Systematic Literature Review of User-Centric QoE and QoS Evaluation Methods in Video Streaming Services” (DOI: 10.62527/joiv.10.5.4640). Published on September 30, 2026, the study was authored by Fahmi Candra Permana, Fetty Fitriyanti Lubis, Armein Z. R. Langi, and Yoanes Bandung. The research provides a comprehensive analysis of existing methods for evaluating video streaming quality and identifies emerging opportunities for developing more user-centered assessment approaches.
Beyond Technical Performance in Video Streaming Evaluation
Traditional video streaming quality evaluation primarily relies on Quality of Service (QoS) indicators, including bandwidth, latency, packet loss, and network reliability. However, technical performance alone cannot fully represent user satisfaction.
Quality of Experience (QoE) introduces a broader perspective by incorporating four principal influencing factors: Content, User, Context, and System. These dimensions collectively capture technical performance, content characteristics, individual expectations, and viewing conditions.
Figure 1. Four principal factors influencing Quality of Experience: Content, User, Context, and System. Source: Figure 2 of the published article.
This multidimensional perspective motivates the development of evaluation methods that integrate technical measurements with real-world user perceptions.
Systematic Review of Video Streaming Quality Assessment Methods
The research employed a hybrid systematic literature review combining systematic mapping, PRISMA-based study selection, and bibliometric analysis.
From 1,105 publications identified across academic databases, 120 relevant studies were categorized, with 43 primary studies forming the basis for detailed thematic analysis. The reviewed literature covered research published between 2018 and 2023.
The analysis identified five major research themes encompassing QoE/QoS evaluation, crowdsourcing, machine learning-based QoE prediction, measurement metrics, and user perception-based assessment methods.
Emerging Trends in User-Centered QoE Research
The findings reveal a growing shift from conventional network-oriented evaluation toward hybrid approaches integrating technical performance, subjective assessments, and intelligent data analysis.
Bibliometric visualization using VOSviewer identified interconnected research themes involving user perception, user engagement, machine learning, and social networks.
Figure 2. Keyword co-occurrence visualization illustrating thematic relationships among QoE, user perception, user engagement, and social network analysis. Source: Figure 8 of the published article.
These relationships highlight increasing research interest in using social media interactions and sentiment analysis to understand users’ experiences with video streaming services. Such approaches offer opportunities to complement conventional subjective assessments and support more scalable, data-driven QoE evaluation.
Future Opportunities for Intelligent Multimedia Services
The study identifies three promising directions for future QoE research: developing measurement models based on user perceptions, implementing data-driven QoE monitoring and prediction, and optimizing multimedia services through QoE-based recommendations.
Figure 3. Research opportunities in multimedia QoE management, encompassing modeling, monitoring, and service optimization. Source: Figure 9 of the published article.
These directions provide a foundation for developing adaptive evaluation systems that combine user feedback, machine learning, and technical service indicators.
Through this publication, PPTIK ITB contributes to advancing research on multimedia service quality by establishing a systematic understanding of existing evaluation methods and identifying opportunities for more intelligent, efficient, and user-centered video streaming services.
