• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1057-1064
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• 2007

From the view of natural language process, quantitative linguistic analysis is a linguistic study relying on statistical methods, and is a mathematical linguistics in an attempt to discover various linguistic characters by interpreting linguistic facts quantitatively through statistical methods. In this study, I would like to introduce a quantitative linguistic analysis method utilizing a computer and statistical methods on literary works. I also try to introduce a use of SynKDP, a synthesized Korean data process, and show the relations between distribution of linguistic unit elements which are used by the hero in a novel #Sassinamjunggi# and theme analysis on literary works.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3675-3684
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• 2021

Human reliability analysis (HRA) is a proactive approach to model and evaluate human systematic errors, and has been extensively applied in various complicated systems. Dependence assessment among human errors plays a key role in the HRA, which relies heavily on the knowledge and experience of experts in real-world cases. Moreover, there are ofthen different types of uncertainty when experts use linguistic labels to evaluate the dependencies between human failure events. In this context, this paper aims to develop a new method based on linguistic hesitant fuzzy sets and the technique for human error rate prediction (THERP) technique to manage the dependence in HRA. This method handles the linguistic assessments given by experts according to the linguistic hesitant fuzzy sets, determines the weights of influential factors by an extended best-worst method, and confirms the degree of dependence between successive actions based on the THERP method. Finally, the effectiveness and practicality of the presented linguistic hesitant fuzzy THERP method are demonstrated through an empirical healthcare dependence analysis.

• Korean Journal of Cognitive Science
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• v.16 no.2
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• pp.93-121
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• 2005

Substantial amounts of research have been accumulated by the attempt to use linguistic styles as the dependent measure in conducting psychological research. This research was condoned to develope a Korean text analysis program(KLIWC) based on the English text analysis program, LIWC(Linguistic Inquiry and Word Count), and the program reflects the Korean linguistic characteristics and culture that is related with language. We made it possible to analyze agglutinative phrase of many morphemes by linguistic tagging, and basic form dictionary and inflection rule were built. In addition, the face-saving weeds and emotional words were included as the analysis variables. The process of development and characteristics of Korean text analysis have been reviewed, and future direction for the improvement of the program has been discussed.

• Language and Information
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• v.8 no.2
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• pp.131-147
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• 2004

the two Korean causal conjunctive suffixes, -nula(ko) and -nun palamey, based on corpus linguistic analysis. Many of the linguistic accounts available, both in pedagogical reference and in the literature on linguistics, provide incomplete analyses of these suffixes, based on fabricated linguistic data. Using naturally occurring, real linguistic data, this paper examines the syntactic and semantic structures of the two causal suffixes through a consideration of three areas of corpus linguistic analysis: token frequencies, collocations, and semantic prosody. An analysis based on concordance data reveals that the two causal connectives, -nula(ko) and -nun palamey, have more differences than similarities in terms of syntactic and semantic constraints. The idiosyncratic structures of the two suffixes are discussed in terms of same subject condition, verb selection, same agent condition, synchronicity condition, and negative semantic prosody.

• Language and Information
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• v.14 no.2
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• pp.33-46
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• 2010

This paper introduces a new linguistic-focused approach for sentiment analysis (SA) of Korean. In order to overcome shortcomings of previous works that focused mainly on statistical methods, we made effective use of various linguistic features reflecting the nature of Korean. These features include contextual shifters, modal affixes, and the morphological dependency of chunk structures. Moreover, in order to eschew possible confusion caused by ambiguous words and to improve the results of SA, we also proposed simple adjustment methods of word senses using KOLON ontology mapping information. Through experiments we contend that effective use of linguistic features and ontological information can improve the results of sentiment analysis of Korean.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.1
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• pp.5-15
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• 1997

This paper mentions a fault tree analysis using not probability but natural language and fuzzy theory, Reliability estimate of each basic event and dependence level estimate among subsystems are expressed by linguistic terms. Analysis results are also expressed by natural language. The meaning of linguistic terms is expressed by a fuzzy set. In the presented analysis approach parametrized operations of fuzzy sets are considered so that analyst's subjectivity can be introduced into the analysis. This paper gives the Chernobyl accident as an example of the fuzzy fault tree analysis using linguistic terms.

• Journal of Smart Tourism
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• v.1 no.3
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• pp.21-29
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• 2021

This study explored the relationship between post types and linguistic characteristics in marketer-generated content and social media engagement to find the optimized content to enhance social media engagement level. Post data of 23,588 marketer-generated content were collected from 50 states' destination marketing organization Facebook pages in the United States. The collected data were analyzed by employing social media analytics, linguistic analysis, multivariate analysis of variance, and discriminant analysis. The results showed that there are significant differences in both engagement indicators and linguistic scores among the three post types. Based on research findings, this research not only provided researchers with theoretical implications but also suggested practitioners the most effective content designs for travel destination marketing in Facebook.

• Journal of The Korean Association of Information Education
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• v.16 no.4
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• pp.475-482
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• 2012

A class is a complex and interactive process between a teacher and students. This paper describes a software design and implementation of the tool easily to analyze and quantize teaching ability. Our proposed software is implemented based on Flanders linguistic method. The software can easily represent the linguistic analysis results by abstracted graphic drawings. We carry out the performance test of our implemented software targeting incumbent teachers. In the experimental, we could demonstrate the effectiveness and practicality of our implemented software.

• English Language & Literature Teaching
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• v.9 no.spc
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• pp.113-129
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• 2003

This study aims to probe for ideological construction within the linguistic structure of newspaper reporting. The study focuses on news reports relating the issue of new IOC chairman election in English version of four mainstream newspaper published in Korea: The Donga Daily News, The Jungang Daily News, The Chosun Daily News, and The Korea Times. The analysis of these reports adheres to the analytic paradigm of critical linguistic analysis and shows how the newspaper articulate conflicting ideological positions in their reports of new IOC chairman election. The analysis demonstrates how the event of new IOC chairman election is naturalized in racist accounts. This study is important for understanding the constructive nature of language practices. The study concludes with a discussion to explain the need for critical awareness in choosing right teaching material, considering that news reports are widely accepted as an authentic material for English education.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.8
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• pp.343-348
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• 2019

In recent years, extractive summarization systems based on end-to-end deep learning models have become popular. These systems do not require human-crafted features and adopt data-driven approaches. However, previous related studies have shown that linguistic analysis features such as part-of-speeches, named entities and word's frequencies are useful for extracting important sentences from a document to generate a summary. In this paper, we propose an extractive summarization system based on deep neural networks using conventional linguistic analysis features. In order to prove the usefulness of the linguistic analysis features, we compare the models with and without those features. The experimental results show that the model with the linguistic analysis features improves the Rouge-2 F1 score by 0.5 points compared to the model without those features.