Technology-Enhanced Suggestions for Customizing CLIL Materials: With the Topic of Virtual Humans

This study investigated the intricate dynamics surrounding the public reception of the virtual influencer Rozy in South Korea, utilizing a text-mining approach on data extracted from popular platforms such as Naver, YouTube, and Instagram. Drawing from a vast corpus of user comments, the research revealed significant differences in public sentiments and narratives, a phenomenon distinctly modulated by the individual characteristics of each platform and varying degrees of user anonymity: Naver, offering the highest level of user anonymity, resulted in a lot of critical comments towards the virtual influencer, while YouTube centered more on technological discourse and Instagram gathered positive engagements. Additionally, this study showcased the development of an English wordlist by utilizing Python libraries for collecting corpus data from platforms such as Google News, YouTube, and Quora, which can be useful sources for learners in CLIL classrooms, fostering deeper engagement with the emergent influencer culture. It emphasized the necessity of a nuanced approach in data collection and analysis, recognizing the distinct characteristics of each platform and the content they host, thereby contributing significantly to CLIL pedagogy through the creation of an English wordlist developed from authentic materials, fostering enhanced learner engagement.