Supplementary Material.xlsx

As social platforms see a surge in diverse user-generated content (UGC), determining high-quality contributions becomes crucial, particularly for educational purposes. This paper explores how the quality of educational UGC shapes user experiences, engagement, and credibility, proposing a computational framework called ELECTRE-SORT. Using a dataset of 16 educational UGCs from various platforms, we categorize content based on quality criteria and find that the majority fall into the medium quality category. This underscores the importance of prioritizing quality over quantity for platform success. Finally, we provide a sensitivity analysis and suggest future research directions.