Digital Discourse and Linguistic Proficiency: Sentiment Analysis of YouTube Comments in Informal English Learning Experiences

This study investigates the potential of virtual communities of practice (VCoP) in English language education through sentiment analysis of YouTube comments on videos by Oliver Ssam (2022) and Moon Ga Young (2023). YouTube enables learners to exchange insights on English pronunciation and multilingual proficiency, fostering an interactive and collaborative learning environment through active engagement in comment sections. Sentiment analysis was conducted using the Sentiment VADER algorithm and Naïve Bayes classifier, achieving 94% and 96% accuracy rates for the respective videos. The study identified five key emotional themes among Korean English learners: positive emotions (“jeong”), negative emotions (“han”), realization, ambivalent emotions, and tolerance. Positive emotions were the most prevalent, encouraging greater engagement in English learning through expressions of approval and admiration. The methodological implications of applying sentiment analysis to English learners’ active engagement in YouTube comments may offer valuable insights for enhancing English education. This study underscores the value of VCoP for informal learning that enhances digital literacy and supports language acquisition beyond traditional classroom settings. By integrating VCoP into formal education, educators can foster active participation and personalized learning experiences. This approach bridges the gap between informal and formal education, offering learners flexible and self-directed opportunities for language learning.