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.

Developing AI-assisted application for pronunciation and speaking evaluation aids in helping students enhancing communicative competency. Recent advancement of speech technology and natural language processing makes it possible to build data-driven computer assisted language learning system with a limited capability of recognizing oral inputs. This paper overviews the needs and development such corpus-based computer assisted system of English learning and suggests a need for more sophisticated corpus construction for intermediate and advanced learners of English who are in need of enhancing their pronunciation and speaking competency.

The purpose of this study is to examine how hedging expressions in terms of lexicon and syntactic structure were presented in English listening test of Korean CSAT as a pragmatic strategy for Korean learners. To achieve this purpose, two questions were raised: Based on English listening test of Korean CSAT, 1) how do hedging expressions appear in terms of lexical structure? and 2) how do hedging expressions appear in terms of syntactic structure? In order to answer the research questions, the items of listening test from 1994 to 2022 were divided into two groups, the monologue and dialogue to figure out differences of their phonetic properties according to Nunan(1991)’s classification. Also, Crompton(1997) and Kim(2008)’s taxonomy of hedges were used because they defined hedging expressions as a pragmatic strategy. This study was analyzed by the corpus program, Antconc. The results indicated that hedging expressions used in the listening test in Korean CSAT appear depending on given taxonomy of hedges differently. First, the lexical hedging expressions were used more frequently than syntactic ones. In addition, these hedging expressions used in the listening test in Korean CAST appear depending on the type of linguistic data differently. Second, the rate of all syntactical hedging expressions in the monologues was approximately six times higher than in the dialogues. Some syntactical hedging expressions also have different meanings depending on the type of linguistic data, even if they are the same forms. More detailed accounts for analyzing are discussed in the paper.

This study is to construct and compare a high frequency word list of different topis in L1 and L2 children’s English newspapers. The Kids Times and My Apple News are selected for L2 children’s English newspapers, and CBBC is chosen for L1 children’s English newspaper. The chosen children’s English newspapers are constructed into text corpus for the analysis of topic-based frequency list extraction. The topics covers five areas: Special Focus, People, Nature & Animals, Sports, International News. The findings are the frequent words concur in both L1 and L2 English newspapers. They are highly co-related to the national curriculum vocabulary list. Discrepancies between L1 and L2 word list can be utilized for inter-cultural awareness learning opportunities.

This study aims to study some similarities and differences in content, vocabulary and linguistic features of maritime safety news and maritime security news in self-built corpora through the two strategies of keyword extraction: comparison against a representative general English corpus and cross-validation. It is found that the content of the maritime safety news is concerned with the safety of operation process, safe regulation, and the recent topic: Covid-19, which is to report the safety of the ship and related personnel. On the other hand, the content of the maritime security news is focused on pirate attacks, robberies, and other external factors of security. Cross-validation shows that maritime safety news prefers to use modal verbs, while maritime security news prefers to use the passive voice. We also explore which syntactic pattern is preferred through adjacent collocates of ‘safety’ and ‘security’ in both of the news. In addition, we investigate their window span (-5 to +5) collocation through examination of several statistical measures to find out similarities and differences between a pair of near-synonyms ‘safety’ and ‘security’ used in the two corpora.

Metadiscourse refers to those aspects of texts which can lead to the construction of writer and reader interaction. Taken this into account, this study set to investigate how men and women used metadiscourse features in social media in the English language context. Being corpus-based in nature, this study privileged a corpus of 145,213 words gathered from such social media as Facebook, Instagram, and Twitter divided by gender of male and female who wrote in English as the language of communication. For analyzing metadiscourse features, Hyland’s classification (2005) was applied that divides metadiscourse features into two main categories of interactive and interactional. The results indicated that in overall both male and female corpora contained more interactional metadiscourse features than interactive. In addition, female corpus contained more metadiscourse features than male corpus. Added to this, it was found that self-mentions were the most frequent instances of metadiscourse features in both male and female corpora. Moreover, it was revealed that although male corpus had instances of code glosses, the female corpus lacked it. The results showed that there was a statistically significant difference between males and females in using metadiscourse features. The findings of this research can have useful implications in such areas as gender studies, comparative studies, corpus-based studies, and contrastive linguistics.