• 제목/요약/키워드: dictionaries

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Review of Fish Name on the Fishes of the Family Mugilidae in Korea and Resource Utilization (우리나라 숭어과 어류의 어명 및 자원 활용에 대한 고찰)

  • Ko, Eun Young;Park, Jong Oh;Lee, Kyoung Seon
    • Journal of Marine Life Science
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    • 제4권2호
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    • pp.96-105
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    • 2019
  • The mugilidae fishes are common euryhaline species that live in coastal marine waters to freshwater areas. The taxonomy and nomenclature of the mugilidae fishes still remain unresolved because of their morphological similarities. Among the mugilidae fishes, most commonly consumed in Korea, are grey mullet (Mugil cephalus) and red lip mullet (Chelon haematocheilus). It is generally called 'mullet' without distinguishing between two mullets. Therefore, the aim of this study is to examine the scientific names and common names of mullet species used in Korea from the domestic journals and Korean old documents. The scientific name of grey mullet is M. cephalus, but that of redlip mullet is C. haematocheilus. But the genus of redlip mullet is still mixed with Chelon, Mugil, and Liza. The standard name of two mullet is not distinguished in the Korean dictionary, but they were clearly distinguished in the Japanese, English, and Chinese dictionaries. In the ancient Korean references, the mullet was called 'Chieo' or 'Sueo'. In most of the old literature, the distinction between grey mullet and redlip mullet is not clear. However, in Jasaneobo, it was written separately from grey mullet and redlip mullet, and attaching "ga" was different from now. The Korean standard name of redlip mullet is 'gasungeo', however, the fishermen in Jeollado and Gyoungsangdo call it 'chamsungeo'. Considering the negative perception of 'ga' character, it is proposed to change 'cham(眞)' instead of 'ga(假)' to improve economic value of red lip mullet.

Romance between Women in the Age of 'Feminism Reboot' -Focusing on Biwan seri's Her Simcheong(justoon, 2017-2019) ('페미니즘 리부트' 시대의 여성 간 로맨스 -비완·seri, <그녀의 심청>(저스툰, 2017~2019))

  • Heo, Yoon
    • Journal of Popular Narrative
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    • 제26권4호
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    • pp.183-212
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    • 2020
  • GL(Girls' Love), which deals with romance between women, is considered a small, minor culture in the sub-culture market. Nevertheless, recent 'reboot feminism' in the voice of women in the epic that appears to be the central protagonist is increased, and interest in naturally glIncreasing. It encourages those who declare "post BL" to consume GLs featuring female characters instead of male characters. In an atmosphere where female creators consume female dictionaries who write women's stories and argue that they should expand the scope of their female counterparts, "Her Simcheong," a webtoon that won the 2018 Our Comics Award, explores the possibility of female epic through rewriting myths. Gender norms given to women, such as filial piety and nirvana, all get new names in . A good daughter is a liar, and a good wife has a woman she loves. Besides Simcheong, hit-and-run mothers, Jang Seung-sang's wife and Jang Seung-sang's daughter-in-law also focus on female characters' stories, highlighting solidarity among women to survive in a male-dominated society. In this process, solidarity among women naturally leads to GL imagination. Her Simcheong describes direct sexual contact, such as kissing and hugging among women, as beautiful illustrations, and shows romance between women in a manless world. While solidarity among women is always regarded as 'undangerous' friendship or girlish sensibility, the romance between women in breaks the cultural rules of women's growth novel and women's trade. This reveals the inconsistency of the conspiratorial male solidarity, which has been trading women around hegemony.

The True Identity and Name Change of Jajak-mok, the Wood Species for Woodblock Printing in the Joseon Dynasty (조선시대 목판재료 자작목(自作木)의 실체와 명칭 변화)

  • LEE Uncheon
    • Korean Journal of Heritage: History & Science
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    • 제56권2호
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    • pp.206-220
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    • 2023
  • In the royal publishing process of the Joseon Dynasty, the main species of wood used for woodblock printing was recorded as Jajak-mok. Although the name Jajak-mok may suggest Jajak-namu(white birch), it is presumed to refer to a different type of wood than Jajak-namu based on its recorded habitat and usage in historical documents. The aim of this paper is to clarify that during the Joseon Dynasty, the term Jajak-mok referred to Geojesu-namu (Korean birch), while Jajak-namu was called Hwa-mok(樺木). Additionally, this paper explores how the term Jajakmok eventually became the name of white birch, Jajak-namu, used today. In the mid-18th century, Japan used the character 樺(hwa) to refer to Beot-namu(Sargent cherry). As Japanese encyclopedias entered Joseon, the term Hwa-mok began to refer to both Beot-namu and Jajak-namu, which is also called Bot-namu. Since the pronunciation of Boet-namu and Bot-namu are similar, the two trees were eventually unified under the name Boet-namu. In the 20th century, the official names of three trees were established. According to notifications issued by the Ministry of Agriculture and Commerce of the Korean Empire in 1910 and the Governor-General of Chosen in 1912, Hwa-mok(white birch) was renamed asJajak-namu. In 1968, Beot-namu(Sargent cherry) retained its original name, and Jajak-mok(Korean birch) was remained . In modern Chinese character dictionaries, the meaning of 樺(hwa) is listed as "1. Beot-namu(Sargent cherry), 2. Jajak-namu(white birch)." From this, we can infer the historical background in which the names of these three trees were mixed up.

Investigating Dynamic Mutation Process of Issues Using Unstructured Text Analysis (비정형 텍스트 분석을 활용한 이슈의 동적 변이과정 고찰)

  • Lim, Myungsu;Kim, Namgyu
    • Journal of Intelligence and Information Systems
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    • 제22권1호
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    • pp.1-18
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    • 2016
  • Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.

A study of the destructive styles from Contemporary Paintings - Focused on distinguishing enmity-destruction and self-destruction - (현대회화에서 드러난 해체의 형식론에 관한 연구 -타의적 해체와 자의적 해체의 성격규정을 중심으로-)

  • Park Ki-Woong
    • Journal of Science of Art and Design
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    • 제7권
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    • pp.5-63
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    • 2005
  • Generally, the meanings of destruction are related in the meaning of demolition, breakdown, into fragments ... and so on, and the similar meanings are twist, crush, demolish, split, cut, into pieces , break up ... etc. Further, it has related in the cruelty and destructive heart which are linked with orgy, Sadism, Necrophilia and so on. The meanings are also expressed by the initial , which are deprivation, deface, defame, deform, degrade, delegitimize, denounce , deride, destroy, devalue, as well as debase, debunk, declaim, declassify, decry, delete, denigrate, deprecate, despise or detract ...and so on. Dario Gamboni has discussed the meaning in his book as two categories Iconoclasm and Vandalism. And the similar meanings could be found in the words which has the initial of , like abase, abate, abhor, abjure, abolish, abridge, abuse ...and so on. Even though the distinct meanings of Iconoclasm and Vandalism, it is not easy to distinguish clearly between the differences when the results are accomplished in contemporary paintings because of the similarity of the results. In korean vocabulary there are no similar words to distinguish between the meanings of destruction and deconstruction, and the deconstruction is not recorded in the general dictionaries. However the meaning of is diminishing, separation, contrast and so on. So the unification of the word as do-construction is not construct, minus construction, reverse construction. And Vincent Ditch explained that there are the meaning of destroy the text. From Jacques Derrida, the deconstruction strategy is to criticise the world of traditional metaphysics and logocentrism, and not to reconstruire the philosophical meaning of texts but $d\'{e}construire$ them. And Saussure emphasized that the signifers could have more meaning that there can be more signified in traditional texts in the art. as a result, deconstruction is explained that there are many signified meanings in a signifer. In this thesis , from using the meanings of destruction and deconstruction, to distinguish the expressive skills in contemporary art works are arising. Therefore, special methods which are linked in the destruction styles are selected. As a result, the two different purposes of destruction is arising, one is enmity destruction and the other is self destruction another word, auto destruction or destruction to create The enmity destruction can be distinguished by the two category Iconoclasm and Vandalism. They come from the moment of different historical aspect is arising and want to attack the Icon or masterpiece this concept is from the study of John Philips and especially iconoclasm is linked with religious and artistic heart, but Vandalism is come from the political attack. Sometime, this distinguish is not clearly arising, because the two aspects are co-related in the attack. As a result, firstly, the Iconoclastic controversy had arisen in the methods of Dadaism which has developed by Man Ray, Francis Picabia and Marcel Duchamp. They want to attack the pre-established master-pieces and painting spaces, and they had 'non-artistic attitude' not to be art. Since 1980, the German artist Anselm Kiefer adapted the methods and made them his special skills so he had tried to paint tough brush strokes and draw with hugh pallette image line and fire and water images , they can be the image attack as the Iconoclasm. secondly, the model of vandalism is to be done by hammer, drill, canon and so on. the method is to attack the content of painting. Further, the object of destruction is bound by cords and iron lings to demolish or to declare the authority of pre-statues; it symbolize the pre-authority is gone already. Self-destruction based paintings are clearly different in the purpose of approaching the art work. First of all, they can be auto-destruction, creative destruction and metamorphosis destruction, which is linked with the skill the material aspect and basic stature, and sign destruction or signifier destruction, which is link with the inner meaning destruction that is considered as the Semiotical destruction in post-modern paintings. Since 1960, the auto destruction is based on the method of firing, melting, grinding and similar skills, which is linked with Neo-Dada and reverse-assemblage. Metamorphosis destruction is strongly linked with the basic inner heart price and quality, so it can be resulted in the changedness of expectation and recognition. Tony Cragg has developed the skills to metamorphose the wood as stone or iron as cloth and stone as sponge and rubber and so on. The researcher has developed the same style in the series of since 2003. The other self-destructive methods are found in the skill of sign destruction. In the methods the meaning of the art is not fixed as one or two, but is developed multi-meaning and differ from original starting situation, so Jacques Derrida called the difference meaning in deconstruction. It is the destruction of textes. These methods are accomplished by David Salle, Francesco Clemente, and recently Tracy Emin, who has developed the attacking heart in the spectators' emotion. Sometime in the method of self-destruction, it is based on horror and shock, the method is explored by Demian Hirst and Jakes and Dinos Chapman. Their destructive styles stimulate ambivalent heart and destroy original sign of girl and animals.

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Comparative Analysis of Medical Terminology Among Korea, China, and Japan in the Field of Cardiopulmonary Bypass (한.중.일 의학용어 비교 분석 - 심폐바이패스 영역를 중심으로 -)

  • Kim, Won-Gon
    • Journal of Chest Surgery
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    • 제40권3호
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    • pp.159-167
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    • 2007
  • Background: Vocabularies originating from Chinese characters constitute an important common factor in the medical terminologies used 3 eastern Asian countries; Korea, China and Japan. This study was performed to comparatively analyze the medical terminologies of these 3 countries in the field of cardiopulmonary bypass (CPB) and; thereby, facilitate further understanding among the 3 medical societies. Material and Method: A total of 129 English terms (core 85 and related 44) in the field of CPB were selected and translated into each country's official terminology, with help from Seoul National University Hospital (Korea), Tokyo Michi Memorial Hospital(Japan), and Yanbian Welfare Hospital and Harbin Children Hospital (China). Dictionaries and CPB textbooks were also cited. In addition to the official terminology used in each country, the frequency of use of English terms in a clinical setting was also analyzed. Result and Conclusion: Among the 129 terms, 28 (21.7%) were identical between the 3 countries, as based on the Chinese characters. 86 terms were identical between only two countries, mostly between Korea and Japan. As a result, the identity rate in CPB terminology between Korea and Japan was 86.8%; whereas, between Korea and China and between Japan and China the rates were both 24.8%. The frequency of use of English terms in clinical practices was much higher in Korea and Japan than in China. Despite some inherent limitations involved in the analysis, this study can be a meaningful foundation in facilitating mutual understanding between the medical societies of these 3 eastern Asian countries.

Korean Word Sense Disambiguation using Dictionary and Corpus (사전과 말뭉치를 이용한 한국어 단어 중의성 해소)

  • Jeong, Hanjo;Park, Byeonghwa
    • Journal of Intelligence and Information Systems
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    • 제21권1호
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    • pp.1-13
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    • 2015
  • As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

A quantitative study on the minimal pair of Korean phonemes: Focused on syllable-initial consonants (한국어 음소 최소대립쌍의 계량언어학적 연구: 초성 자음을 중심으로)

  • Jung, Jieun
    • Phonetics and Speech Sciences
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    • 제11권1호
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    • pp.29-40
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    • 2019
  • The paper investigates the minimal pair of Korean phonemes quantitatively. To achieve this goal, I calculated the number of consonant minimal pairs in the syllable-initial position as both raw counts and relative counts, and analyzed the part of speech relations of the two words in the minimal pair. "Urimalsaem" was chosen as the object of this study because it was judged that the minimal pair analysis should be done through a dictionary and it is the largest among Korean dictionaries. The results of the study are summarized as follows. First, there were 153 types of minimal pairs out of 337,135 examples. The ranking of phoneme pairs from highest to lowest was 'ㅅ-ㅈ, ㄱ-ㅅ, ㄱ-ㅈ, ㄱ-ㅂ, ㄱ-ㅎ, ${\ldots}$, ㅆ-ㅋ, ㄸ-ㅋ, ㅉ-ㅋ, ㄹ-ㅃ, ㅃ-ㅋ'. The phonemes that played a major role in the formation of the minimal pair were /ㄱ, ㅅ, ㅈ, ㅂ, ㅊ/, in that order, which showed a high proportion of palatals. The correlation between the raw count of minimal pairs and the relative count of minimal pairs was found to be quite high r=0.937. Second, 87.91% of the minimal pairs shared the part of speech (same syntactic category). The most frequently observed type has been 'noun-noun' pair (70.25%), and 'vowel-vowel' pair (14.77%) was the next ranking. It can be indicated that the minimal pair could be grouped into similar categories in terms of semantics. The results of this study can be useful for various research in Korean linguistics, speech-language pathology, language education, language acquisition, speech synthesis, and artificial intelligence-machine learning as basic data related to Korean phonemes.

The prediction of the stock price movement after IPO using machine learning and text analysis based on TF-IDF (증권신고서의 TF-IDF 텍스트 분석과 기계학습을 이용한 공모주의 상장 이후 주가 등락 예측)

  • Yang, Suyeon;Lee, Chaerok;Won, Jonggwan;Hong, Taeho
    • Journal of Intelligence and Information Systems
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    • 제28권2호
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    • pp.237-262
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    • 2022
  • There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.