The purpose of this study is to analyze how particles of English are translated in Korean and discuss whether the results of the analysis are consistent with the cognitive semantic approach about English particles. First, UP and OUT were selected for the subjects of the study. Then, to obtain the most appropriate data for the purpose of the study, eight films were selected from the OTT platform Netflix and the text as data were collected by extracting subtitles. We examined the collected translation data, investigated what translation strategies the English particles and phrasal verbs in the data were translated through, and produced statistics. Finally, we confirmed that the results of the analysis support cognitive semantic view on English particles that particles in phrasal verbs are not arbitrary, and we made a brief generalization of the results of the analysis.scale.

The present study is based on a self-built Maritime English Law Corpus compared with BNC Baby as a reference corpus to explore some homogeneous features of four different maritime legal genres through the comparison of two different keyword analyses: corpus frequency-based keyword analysis and text dispersion-based keyword analysis. A comparison of keyword lists of four legal genres by using a cross-validation is also conducted to explore unique characteristics of each genre. The results show that two keyword methods generated both shared words and unshared words. According to the two criteria of keywords, we concluded that text dispersion-based keyword analysis is much better than traditional corpus frequency-based keyword analysis because the former meets both the content-distinctiveness of maritime-related keywords and the content-generalisability of law content keywords as well as showing more homogeneous maritime legal features than the latter.

This study analyzed the factors affecting the axiological semantic characteristics of Korean metaphors from the perspectives of cognitive linguistics and pragmatics. To this end, the related factors were classified into embodied characteristics, morality, and cultural relativistic characteristics. Finally, the face threatening aspects of each factor were analyzed through daily conversation corpus data. According to the results, many of the Korean metaphors with negative meanings were derived from proverbs or idiomatic expressions. In addition, the threat to face caused by metaphors containing cultural negativity was significant. In particular, the metaphorical expressions of animals or objects had a relatively high threat to face, as ontological negativity was added to idiomatic negativity. Nevertheless, the axiological semantic and embodied characteristics inherent in Korean metaphors were largely based on the universality suggested by previous studies. However, despite this universality, learners from other cultures appear to have difficulties in interpreting the meaning of Korean metaphors. Therefore, there is a need to prepare a systematic plan to minimize the pragmatic failure of Korean language learners

Choi, J.M.(2023). A gender identification of Korean blog writers through machine learning. Gender identification of texts is a subfield of author analysis; author profiling. This study is an preliminary experiment on an automatic gender detection model for the 1,162 posts of 13 blog owners. As linguistic features, four types of n-gram (word, function word, character, and POS), phoneme frequency, and four lexical sets were chosen, and the support vector machine was adopted as a classifier. The classification accuracy ranged from 54% to 99% depending on the feature type. But the best performing model was produced(obtained) when all the features were inputted combined minus word n-grams. The most salient features distinguishing female from male writers were found to be the first person pronouns( (‘나(I, me)’ and ‘내(+*)’ for females vs. 저(-*)’ and 제(-)’ for males)) and sentence endings(‘다, ‘ᄂ다’ and ‘었다’ for females vs. , ‘습니다’, ‘ᄇ니다’, ‘습니다’, ‘네요’for males). This preliminary study could lead to further research into the gender language variations, and contribute to the development of a stable and robust author profiling system.