Like or Not to Like: An Usecase of Vietnamese Street Food Videos on YouTube

摘要

Vietnamese street food has gained global popularity through platforms like YouTube, where creators are incentivized to post videos on specific topics, including street food. Efficient video editing has become essential for YouTubers. This study analyzed 1,507 videos and gathered insights from 213 respondents to identify the factors that shape viewer preferences and highlight key video features for creators. The study's key finding was the strong synergy between visual elements and linguistic richness, emphasizing the connection between storytelling and what appears on screen. Using machine learning, we examined visual, linguistic, and acoustic features, achieving a 70.5% accurate predictive model. Compared to the baseline 50%, these insights led to personalized recommendations for street food content creators, offering strategies to enhance viewer engagement. Our automated recommendation system bridges data-driven insights with content creation, elevating Vietnamese street food on the global stage and celebrating the blend of local culture and technology.