KJCKorea
Journal Central

This paper examines the language of comments on K-pop YouTube videos from the 1970s to the 1990s. Specifically, it analyzes the comments on compilation videos of songs by Cho Yong-pil and Hye-euni, the most popular of that era, focusing on the topics discussed and the titles used for the two singers. The analysis reveals that netizens frequently post comments in five main thematic categories. In ‘Sharing Memories’ and ‘Celebrating and Encouraging’ categories, netizens engage with one another, sharing their feelings as member of a temporary community. Regarding the use of address terms, netizens are found to treat Cho Yong-pil with more respect and reverance than Hye-euni, while also using they friendlier titles for him. This difference is interpreted as a result of factors such as the age and gender differences between the two singers, variations in name composition, career continuity, and levels of popularity. The study suggests that netizens who engage with YouTube music videos are not merely interested in the video content but also express their attitudes toward the featured artists and interact with other viewers.

This paper aims to test deep-learning-based Korean language models’ capacity to learn and detect social registers embedded in speech data, specifically age, gender, and regional dialects. A comprehensive understanding of linguistic phenomena requires contextualizing speech based on speakers’ age, gender, and geographic background, along with the processing of syntactic structures. To bridge the gap between human language understanding and model processing, we fine-tuned three representative Korean language models—KR-BERT, KoELECTRA-base, and KLUE-RoBERTa-base—using transcribed data from 4,000 hours of speech by middle-aged and elderly Korean speakers. The findings reveal that KoELECTRA-base outperformed the other two models across all social registers, which is likely attributed to its larger vocabulary and parameters size. Among the dialects, the Jeju dialect showed the highest accuracy in inference, which is attributed to its distinctiveness, making it easier for the models to detect. In addition to the fine-tuning process, we have made our fine-tuned models publicly available to support researchers interested in Korean computational sociolinguistics.

In this paper, I explore the complex domain of counterfactuality, arguing for its recognition as a discrete grammatical category. My analysis is based on the premise that counterfactuality, as a linguistic construct, encompasses propositions and scenarios that diverge from the empirical realities of our world. I then examine the use of counterfactual expressions in both subordinate clauses and main clauses, with a particular focus on their prevalence in subordinate clauses. These expressions are carefully categorized into three distinct types according to their semantic nature: conditional construction, concessive construction and contrastive construction. Finally, the functions of counterfactual expressions are delineated, revealing their multifaceted roles in serving emotional, preparatory, and inferential purposes within communication.