• 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.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.541-548
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• 2016

The use of social media is already essential as a source of information for listening user's various opinions and monitoring. We define social 'risks' that issues effect negative influences for public opinion in social media. This paper aims to discriminate various linguistic features and reveal their effects for building an automatic classification model of social risks. Expecially we adopt a word embedding technique for representation of linguistic clues in risk sentences. As a preliminary experiment to analyze characteristics of individual features, we revise errors in automatic linguistic analysis. At the result, the most important feature is NE (Named Entity) information and the best condition is when combine basic linguistic features. word embedding, and word clusters within core predicates. Experimental results under the real situation in social bigdata - including linguistic analysis errors - show 92.08% and 85.84% in precision respectively for frequent risk categories set and full test set.

• Asia Pacific Journal of Corpus Research
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• v.3 no.1
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• pp.21-34
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• 2022

This study aims to apply corpus-based approach to analyze The Yellow Wall-Paper and Herland written by Charlotte Perkins Gilman, a women's rights activist in the late nineteenth-century America. Although both works have attracted feminists' attention to the woman question that concerned Gilman, discussion on her language features and their relation to the literary themes of these two works is still in need. In this corpus-based analysis, we argue that the main themes of different literary works can be revealed through linguistic patterns identified by number and gender features of nouns and pronouns in the contrast of two works and a balanced corpus. The linguistic features (number and gender) have been related with two themes, the 'group and individual' and the 'feminine and masculine', and are further interpreted in terms of mothering and feminine consciousness. By adopting linguistic approach, our study provides quantitative and qualitative evidence to verify the established themes and arguments of these literary texts.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.49-55
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• 2019

The character dialogue created by AI is unnatural when compared with human-made dialogue, and it can not reveal the character's personality properly in spite of remarkable development of AI. The purpose of this paper is to classify characters through the linguistic style and to investigate the relation of the specific linguistic style with the personality. We analyzed the dialogues of 92 characters selected from total 60 movies categorized four movie genres, such as romantic comedy, action, comedy and horror/thriller, using Linguistic Inquiry and Word Count (LIWC), a text analysis software. As a result, we confirmed that there is a unique language style according to genre. Especially, we could find that the emotional tone than analytical thinking are two important features to classify. They were analyzed as very important features for classification as the precision and recall is over 78% for romantic comedy and action. However, the precision and recall were 66% and 50% for comedy and horror/thriller. Their impact on classification was less than romantic comedy and action genre. The characters of romantic comedy deal with the affection between men and women using a very high value of emotional tone than analytical thinking. The characters of action genre who need rational judgment to perform mission have much greater analytical thinking than emotional tone. Additionally, in the case of comedy and horror/thriller, we analyzed that they have many kinds of characters and that characters often change their personalities in the story.

• 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.

• English Language & Literature Teaching
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• no.6
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• pp.113-142
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• 2000

In order to obtain a better understanding of L2 learners, transitional knowledges, it is very important and necessary to have a better knowledge of interlanguage. According to Corder, the role of interlanguage in English education holds significance to (1) for language teachers, (2) for language learners themselves, and (3) for language textbook compilers. To me the significance of interlanguage in English education can be described in terms of not only language teachers, learners themselves, textbook writers and compilers but pure linguists, applied linguists, school authorities as well as parents. For language learners themselves a clear understanding of interlanguage results in students being receptive to language input, and the avoidance of mental block, and low levels of foreign language anxiety. Native speakers of English (NSE) reflect not only linguistic features but also psychological, socio-linguistic, and discourse features when engaged in communication activities. This means that L2 learners are introduced to these different features, especially pragmatic features which are different from their mother tongue or L1 when engaged in communication with NSE. Hence the importance of interlanguage pragmatics should be recognized. It is very important that teachers of English should have a better understanding of interlanguage and present L2 learners with their interlanguage features so they can avoid any misunderstandings such features may cause when conversing with NSS. It should also be noted that interlanguage can form the foundation of language acquisition theory and linguistic analysis.

• Journal of the Korean earth science society
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• v.31 no.1
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• pp.36-50
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• 2010

The purpose of this study is to investigate the aspect of variation of the texts in elementary and secondary school science textbooks at each grade level in terms of linguistic features. Data included some of the written texts related to 'Volcano and Earthquake' in Korean elementary and secondary school science textbooks in the seventh National Curriculum. The written texts were comparatively analyzed in terms of textual meaning, interpersonal meaning, and ideational meaning. Results revealed that there were different structures and linguistic features of the texts in school science textbooks depending on the grade level. Therefore, we argue that the differences in this study may make students feel difficult and strange when they read and understand science textbooks. We suggest that science teachers need to play the role of a mediator between students' understanding and the structural features of the scientific language in science learning.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.15-18
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• 2002

Prosodic features of speech are known to play an important role in the transmission of linguistic information in human conversation. Their roles in the transmission of para- and non- linguistic information are even much more. In spite of their importance in human conversation, from engineering viewpoint, research focuses are mainly placed on segmental features, and not so much on prosodic features. With the aim of promoting research works on prosody, a research project 'Prosody and Speech Processing' is now going on. A rough sketch of the project is first given in the paper. Then, the paper introduces several prosody-related research works, which are going on in our laboratory. They include, corpus-based fundamental frequency contour generation, speech rate control for dialogue-like speech synthesis, analysis of prosodic features of emotional speech, reply speech generation in spoken dialogue systems, and language modeling with prosodic boundaries.

• Journal of Digital Convergence
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• v.13 no.5
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• pp.187-194
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• 2015

Various linguistic knowledge resources are required in order that machine can understand diverse variation in natural languages. This paper aims to devise an automatic construction method of linguistic resources by reflecting characteristics of online contents toward continuous expansion. Especially we focused to build NE(Named-Entity) dictionary because the applicability of NEs is very high in linguistic analysis processes. Based on the investigation on Korean Wikipedia, we suggested an efficient construction method of NE dictionary using the syntactic patterns and structural features such as metadatas.