• Asia Pacific Journal of Corpus Research
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• v.2 no.1
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• pp.23-34
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• 2021

This research examines Japanese non-native speakers' (JNNS) modal auxiliary verb use from two different perspectives: frequency of use and preferences for modalities. Additionally, error analysis is carried out to identify errors in modal use common among JNNSs. Their modal use is compared to that of English native speakers within a spoken dialogue corpus which is part of the International Corpus Network of Asian Learners' English. Research findings show at a statistically significant level that when compared to native speakers, JNNSs underuse past forms of modals and infrequently convey epistemic modality, indicating the possibility that JNNSs fail to express their opinions or thoughts indirectly when needed or to convey politeness appropriately. Error analysis identifies the following three types of common errors: (1) the use of incorrect tenses of modal verb phrases, (2) the use of inflected verb forms after modals, and (3) the non-use of main verbs after modals. The first type of error is largely because JNNSs do not master how to express past meanings of modals. The second and third types of errors seem to be due to first language transfer into second language acquisition and JNNSs' overgeneralization of the subject-verb agreement rules to modals respectively.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.4
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• pp.75-93
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• 2020

The purpose of this study is to extract keywords for 'startup' and 'entrepreneurship' from Naver news articles in Korea since 1990 and Google news articles in foreign countries, and to understand the changes in the meaning of entrepreneurship and entrepreneurship in each era It is aimed at doing. In summary, first, in terms of the frequency of keywords, venture sprouting is a sample of the entrepreneurial spirit of the government-led and entrepreneurs' chairman, and various technology investments and investments in corporate establishment have been made. It can be seen that training for the development of items and items was carried out, and in the case of the venture re-emergence period, it can be seen that the youth-oriented entrepreneurship and innovation through the development of various educational programs were emphasized. Second, in the result of vocabulary network analysis, the network connection and centrality of keywords in the leap period tended to be stronger than in the germination period, but the re-leap period tended to return to the level of germination. Third, in topic analysis, it can be seen that Naver keyword topics are mostly business-related content related to support, policy, and education, whereas topics through Google News consist of major keywords that are more specifically applicable to practical work.

• Asia Pacific Journal of Corpus Research
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• v.1 no.2
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• pp.57-72
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• 2020

This study seeks to add to the current understanding of learners' use of modality in argumentative writing. A learner corpus of argumentative essays on four topics was created and compared to native English speaker data from the International Corpus Network of Asian Learners of English (ICNALE). The relationship between learners' use of modal devices (MDs) and the devices' appearance in the school's curriculum was also examined. The results showed that learners relied on a very narrow range of MDs compared to those in previous studies. The frequency of use of MDs varied based on the topic and did not seem to be driven by cultural factors as has been previously suggested. Learners used more hedges than boosters on all topics, contradicting most previous studies. Curriculum was determined to have a direct correlation with MD use, and other important factors may include perception of topic and overreliance on certain MDs over others (the One-to-One principal). This research implies that learners' perception of topic should be explored further as a variable affecting MD use. Curricula should be designed based on frequency of MD use by English native speakers, and learners should receive instruction that teaches the norms of MD use in academic writing. The methodology used in the study to determine correlations between MD use and the curriculum has a wide range of potential applications in the field of Contrastive Interlanguage Analysis.

• Asia Pacific Journal of Corpus Research
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• v.3 no.1
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• pp.35-49
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• 2022

This study examines crosslinguistic influence on the use of concessive conditionals by Japanese EFL learners. Contrastive analysis suggests that Japanese native speakers may overuse the concessive conditional even if due to partial similarities to Japanese concessive conditionals, whose formal and semantic restrictions are fewer than those of English concessive conditionals. This hypothesis is tested using data from the written module of the International Corpus Network of Asian Learners of English (ICNALE). Comparison of Japanese native speakers with English native speakers and Chinese native speakers reveals the following trends. First, Japanese native speakers tend to overuse concessive conditionals compared to native speakers, while similar overuse is not observed in Chinese native speaker data. Second, non-nativelike uses of even if appear in contexts allowing the use of concessive conditionals in Japanese. Third, while overuse and infelicitous use of even if is observed at all proficiency levels, formal errors are restricted to learners at lower proficiency levels. These findings suggest that crosslinguistic influence does occur in the use of concessive conditionals, and that its particular realization is affected by L2 proficiency, with formal crosslinguistic influence mediated at an earlier stage than semantic cross-linguistic influence.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.223-231
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• 2022

The application of computer software into the linguistic analysis of texts proves useful to arrive at concise and authentic results from large data texts. Based on this assumption, this paper employs a Computer-Aided Text Analysis (CATA) and a Critical Discourse Analysis (CDA) to explore the manipulative strategies of positive/negative presentation in Orwell's Animal Farm. More specifically, the paper attempts to explore the extent to which CATA software represented by the three variables of Frequency Distribution Analysis (FDA), Content Analysis (CA), and Key Word in Context (KWIC) incorporate with CDA decipher the manipulative purposes beyond positive presentation of selfness and negative presentation of otherness in the selected corpus. The analysis covers some CDA strategies, including justification, false statistics, and competency, for positive self-presentation; and accusation, criticism, and the use of ambiguous words for negative other-presentation. With the application of CATA, some words will be analyzed by showing their frequency distribution analysis as well as their contextual environment in the selected text to expose the extent to which they are employed as strategies of positive/negative presentation in the text under investigation. Findings show that CATA software contributes significantly to the linguistic analysis of large data texts. The paper recommends the use and application of the different CATA software in the stylistic and corpus linguistics studies.

• International Journal of Advanced Culture Technology
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• v.5 no.4
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• pp.57-62
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• 2017

In this paper, we applied long short term memory(LSTM) for classifying political polarity in cyber public sphere. The data collected from the cyber public sphere is transformed into word corpus data through word embedding. Based on this word corpus data, we train recurrent neural network (RNN) which is connected by LSTM's. Softmax function is applied at the output of the RNN. We conducted our proposed system to obtain experimental results, and we will enhance our proposed system by refining LSTM in our system.

• Annual Conference on Human and Language Technology
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• 2010.10a
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• pp.94-99
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• 2010

This paper is to present how a network between words is formed. Not only have we looked at the distributivity, frequency and strength in connections between related words, but we have also presented some way to shed lights on what this network means to linguistic and social studies. The target source is morpho-analysis components of Trends 21 corpus which cover all newspaper articles from lour major newspapers, including Chosun, Joongang, Donga, and Hankyoreh, issued between 2000 and 2008. Based on nodes, links, and their connectivity indexes - density, degree, and centralizations, we have been able to retrieve and cluster related words forming the network with 20 event nouns. To reduce noise, we have considered the words whose t-score is above 1.64. By conducting both network and statistical analyses, we have presented the network of each event noun.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.69-74
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• 2012

Many internet users attempt to focus on the issues which have posted on social network services in a very short time. When some social big issue or event occurred, it will affect the number of comments and retweet on that day in twitter. In this paper, we propose the method of extracting core events based on timeline analysis, sentiment feature and retweet information in twitter data. To validate our method, we have compared the methods using only the frequency of words, word frequency with sentiment analysis, using only chi-square method and using sentiment analysis with chi-square method. For justification of the proposed approach, we have evaluated accuracy of correct answers in top 10 results. The proposed method achieved 94.9% performance. The experimental results show that the proposed method is effective for extracting core events in twitter corpus.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.691-696
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• 2022

This study explored the lexical sophistication features to distinguish the group membership of English proficiency, using the automatic analysis program of lexical sophistication. A total of 600 essays written by 300 Korean college students were extracted from the ICNALE (International Corpus Network of Asian Learners of English) corpus and a discriminant function analysis was performed using SPSS program. Results showed that the lexical features to distinguish three groups of English proficiency are SUBTLEXUS frequency content words, age of acquisition content words, lexical decision mean reaction time function words, and hypernymy verbs. High-level Korean students used frequent content words from SUBTLEXUS corpus to a lesser degree and produced more sophisticated words that can be learned at a later age and take longer reaction time in lexical decision task, and more concrete verbs.

• Phonetics and Speech Sciences
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• v.10 no.3
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• pp.19-29
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• 2018

We propose to use independent component analysis (ICA) and deep neural network (DNN) to detect music sections in broadcast drama contents. Drama contents mainly comprise silence, noise, speech, music, and mixed (speech+music) sections. The silence section is detected by signal activity detection. To detect the music section, we train noise, speech, music, and mixed models with DNN. In computer experiments, we used the MUSAN corpus for training the acoustic model, and conducted an experiment using 3 hours' worth of Korean drama contents. As the mixed section includes music signals, it was regarded as a music section. The segmentation error rate (SER) of music section detection was observed to be 19.0%. In addition, when stereo mixed signals were separated into music signals using ICA, the SER was reduced to 11.8%.