Cultural Engagement through Music Streaming: Social and Educational Implications of Chinese and Korean OST Recommendation Systems

Abstract

Due to the emergence of the Chinese and Korean TV shows in the global market, there has been a surge in exposure to original soundtrack (OST) music which is commonly listened without the accompanying visuals using streaming technologies. In addition to entertainment, OSTs are significant in emotional appeals, cultural and informal learning on language and national borders. This paper examines how the algorithmic OST recommendation systems can be used to contribute to cross-cultural interaction and increase the emotional and cultural awareness of East Asian media by users. This study will be based on an emotion-sensitive, cross-linguistic recommendation system, and will investigate how music recommendations mediated by a narrative process influence discovery behavior and cultural exposure to digital space users. Sound and emotional features, multiple-language metadata, and interaction by the user are synthesized in order to investigate the influence of recommendation systems in the consumption of music in a culturally diverse environment. Using experimental assessment, emotion-sensitive and multilingual modeling are found to enhance relevance of recommendation especially in sparse and cross-cultural contexts. The implications of the findings to wider social and education OST recommendation systems include the fact, that algorithmic music curation may provide an effective tool to the cultural exchange, emotional literacy, and informal media-based learning in globalized streaming ecosystems.