• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.1
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• pp.14-23
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• 2015

This study applied the network text analysis to reveal the scope and trends of low cost carrier studies. We analyzed low cost carrier research published in Korean journals and news articles. The results showed that there are three clusters in terms of research topics. First dimension consists of articles investigating growth in the low cost carrier industry. The second dimension is associated with service characteristics. The last dimension has strong ties organizational and human resource dimension. We run Krkwic, Krtitle, Netdraw, and Ucinet 6.0 to conduct the network text analysis. This study suggests the direction of low cost carrier research in the future.

• Journal of the Korean Society of Food Culture
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• v.23 no.3
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• pp.336-347
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• 2008

The purpose of this study is to analyze the articles of food and nutrition published in the Yeo-Sung magazines from 1936 to 1940 in Korea. Out of the 67 articles about the food and the nutrition from the Yeo-Sung magazines, 28 (41.8%) of them were about the brief information of food and nutrition news, 16 (23.8%) of them were about the recipes, 6 (9.0%) were about the nutrition information, and 17 (25.4%) of them were about others. As the number of recipes mentioned from the Yeo-Sung magazine was 103, 77 items, the majority, were about the Korean foods, 18 of the Western foods, 6 of Chinese foods, and only 2 of Japanese foods. This result showed that the Japanese colonization didn't seem to influence on Korean tastes and gastronomy. During this period, the modernization caused the numerous changes to our traditional cuisine with introduction of new western menu items and concept of nutrition. The nutrition articles highly recommended eating brown rice, vegetables, tofu, and the white meat. Shin-Young Bang, one of the main authors, insisted that "Cookery is not only the skill, but also the one of the very important academic sciences." showed budding modern cookery sciences in Korea.

• Korean Linguistics
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• v.76
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• pp.83-112
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• 2017

In this paper, newspaper articles were collected through '5.18' keyword search results and the news corpus was constructed from the collected data. In the articles of local newspapers 'Honam' and 'Yeongnam', the ideological differences regarding '5.18' were investigated. The ideological differences of local newspaper discourse through objective figures was analyzed.. The subjects of the newspaper articles, the frequency of nouns and predicates were analyzed. The use and meaning of the intended vocabulary were examined. As a result of analyzing the title of the newspaper article, the discourse written in 'Honam' emphasized the necessity of re - recognition of 5.18. In both regions, the word "Gwangju" is often used. However, 'Gwangju' in 'Honam' newspaper means spiritual space, not physical space. In Honam regional newspapers, there are many vocabularies describing the events such as 'shoot' and 'fire', this calls for recollection and memory of '5.18'. In the analysis of newspaper discourse, the analysis of the contrast between the local newspapers was very insignificant, but, this study was conducted to analyze the discourse among local newspapers.

• Journal of The Korean Association of Information Education
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• v.26 no.6
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• pp.543-552
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• 2022

This study tried to analyze the social perception of news coverage on inclusive education by using big data analysis techniques. News articles were collected according to the 5-year policy period for the development of special education, and news big data was analyzed. As a result, the frequency of media reports during the five-year policy period of special education development from 1998 in the first year to 2022 in the fifth year was steadily increased. During this period, the top topic words in news coverage changed from words conceptualizing simple definitions to words expressing the active will of students with disabilities for the actual right to education. In addition, as a result of emotional analysis of the overall keywords in the inclusive education news coverage, it was found that the positive word ratio was high. Through this study, it can be seen that interest in news coverage on inclusive education is increasing quantitatively in accordance with changes in special education policies, and the demand for inclusive education is being concreted in the direction of guaranteeing the actual right to education of students with disabilities.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.51-57
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• 2021

If a company's actions to save or avoid taxes are judged to be tax evasion rather than legal tax action by the tax authorities, the company will not only pay tax but also non-tax costs such as damage to corporate image and stock price decline due to a series of tax evasion-related news articles. Therefore, this study measures the frequency of occurrence of tax evasion controversial keywords in internet news portal as a factor to measure the severity of the case, and analyzes the effect of the frequency of occurrence on corporate value. In the Korean stock market, we crawl related articles from internet news portal by using keywords that are controversial for tax evasion targeting top companies based on market capitalization, and generate a time series of the frequency of occurrence of keywords about tax evasion by company and analyze the effect of frequency of appearance on book value versus market capitalization. Through panel regression and impulse response analysis, it is analyzed that the frequency of appearance has a negative effect on the market capitalization and the effect gradually decreases until 12 months. This study examines whether the tax evasion issue affects the corporate value of Korean companies and suggests that it is necessary to take these influences into account when entrepreneurs set up tax-planning schemes.

• Journal of the Korean Society for information Management
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• v.4 no.1
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• pp.3-23
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• 1987

This paper describes a question-answering system that can automatically analyze input texts and questions in Korean natural language. The particular texts used for the research were newspaper articles in the specific domain of sports news. The system consists of a set of Cobol programs and an associated set of data files containing lexicon, case grammar, linguistic rules. and data base. This system employs two retrieval functions of fact retrieval and passage retrieval. Therefore input questions can be answered in forms of either sentence or factual data.

• The Journal of the Korea Contents Association
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• v.6 no.10
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• pp.9-16
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• 2006

In this paper, the acoustic model output of CSR(Continuous Speech Recognition) was used to analyze news data News database used in this experiment was consisted of 2,093 articles. Due to the low efficiency of language model, conventional Korean CSR is not appropriate to the analysis of news data. This problem could be handled successfully by introducing post-processing work of recognition result of acoustic model. The acoustic model more robust than language model in Korean environment. The result of post-processing work was made into KIF(Keyword information file). When threshold of acoustic model's output level was 100, 86.9% of whole target morpheme was included in post-processing result. At the same condition, applying length information based normalization, 81.25% of whole target morpheme was recognized. The purpose of normalization was to compensate long-length morpheme. According to experiment result, 75.13% of whole target morpheme was recognized KIF(314MB) had been produced from original news data(5,040MB). The decrease rate of absolute information met was approximately 93.8%.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.41-75
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• 2018

The purpose of this study is to analyze the characteristics of Korean media on the topic of archives & records management based on time-series analysis. In this study, from January, 1999 to June, 2018, 4,680 news articles on archives & records management topics were extracted from BigKinds. In order to examine the characteristics of the media coverage on the archives & records management topic, this study was analyzed to the difference of the press coverage by period, subject, and type of the media. In addition, this study was conducted word-frequency based content analysis and semantic network analysis to investigate the content characteristics of media on the subject. Based on these results, this study was analyzed to the differences of media coverage by period, subject, and type of media. As a result, the news in the field of records management showed that there was a difference in the amount of news coverage and news contents by period, subject, and type of media. The amount of news coverage began to increase after the Presidential Records Management Act was enacted in 2007, and the largest amount of news was reported in 2013. Daily newspapers and financial newspapers reported the largest amount of news. As a result of analyzing news reports, during the first 10 years after 1999, news topics were formed around the issues arising from the application and diffusion process of the concept of archives & records management. However, since the enactment of the Presidential Records Management Act, archives & records management has become a major factor in political and social issues, and a large amount of political and social news has been reported.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.382-385
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• 2007

본 논문은 "X라는 인물은 누구인가?"와 같은 질의어가 주어질 때, X라는 인물에 대한 나이, 직업, 학력 또는 특정 사건에서 X라는 인물의 역할에 대한 정보를 기술하는 문장을 인식하고 추출함으로써 해당 인물에 대한 신문 기사 내용을 요약하는 방법을 제시한다. 질의어 용어에 대해 가능한 많은 관련 문장을 추출하기 위하여 중심 벡터에 기반한 통계적 방법을 적용하였으며, 정확도와 재현율 성능을 개선하기 위해 위키피디어 같은 외부 지식을 사용한 중심 단어의 개선된 가중치 측도를 적용하였다. 실험 대상인 전자신문 말뭉치 상에서 출현 빈도수가 큰 20 인의 IT 인물에 대해 제안한 방법이 개선된 성능을 보임을 알 수 있었다.