• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.628-631
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• 2016

'야구경기 결과에 대해 자동으로 기사를 작성할 수 있는가'에서 본 논문에서는 야구 경기 데이터들을 기반으로 의사결정 트리기법을 사용하여 경기결과의 문맥과 기사작성에 필요한 요소들을 자동으로 추출해보았다. 그 결과 해당경기의 데이터를 가지고 객관적인 야구기사를 생산해 낼 수 있음을 도출해냈다.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.15-32
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• 2016

Online news on the Internet, as published open data, contain facts or opinions about a specific affair and hence influences considerably on the decisions of the general publics who are interested in a particular issue. Therefore, we can predict the people's choices related with the issue by analyzing a large number of related internet news. This study aims to propose a text analysis methodto predict the outcomes of events that take place in a specific place. We used topics of the news articles because the topics contains more essential text than the news articles. Moreover, when it comes to mobile environment, people tend to rely more on the news topics before clicking into the news articles. We collected the titles of news articles and divided them into the learning and evaluation data set. Morphemes are extracted and their polarity values are identified with the learning data. Then we analyzed the sensitivity of the entire articles. As a result, the prediction success rate was 70.6% and it showed a clear difference with other analytical methods to compare. Derived prediction information will be helpful in determining the expected demand of goods when preparing the event.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.806-816
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• 2021

This study aims to describe the reporting patterns of articles on the Emergency Grant for all citizens(EGAC) and compare the reporting attitudes by newspaper companies. The main results are as follows: First, conservative newspapers reported more than four times as much coverage of EGAC as liberal newspapers. Newspaper articles reported during the week of the National Assembly Election Day accounted for about a quarter of the total, and 79.1% of the articles were reported in the political realm of newspapers, and only 2.8% in the social realm. Second, a conservative newspaper reported a critical attitude toward EGAC at 52.6% and favorable articles at 5.3%. On the other hand, in a liberal newspaper, critical articles were 17.1% and favorable articles were 37.1%. The inefficiency of selectivism was reported as the basis for the argument in favor, and concerns about the burden of deterioration in the financial soundness of the opponents were reported the most. Politicians are the most cited sources of information in articles. Finally, in prior to policymaking, the proportion of the media in favor of and against the news was similar, and the proportion of articles with a neutral attitude accounted for more than half. And in the specific method discussion stage, the articles in favor of the article exceeded the proportion of articles on the opposite side.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.19-26
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• 2022

The purpose of this study is to find out how Korea's national image is being established through content analysis of articles related to Korea by the People's Daily in China. There were 253 articles related to Korea published in the People's Daily from 2016 to 2020. Using content analysis methods, articles related to Korea were reviewed in five categories: number of articles, page, source, subject matter, and propensity to report. According to the results of the study, the number of articles related to Korea in the People's Daily has decreased since 2016, and the topic of articles has been in many political and social sectors. In 2016 and 2017, South Korea's decision to deploy THAAD led to a number of articles published in the military sector, and there were negative articles only in military articles. The majority of articles related to Korea in the People's Daily show that it describes Korea positively or objectively. In this regard, the People's Daily shows that it is building a positive image of Korea.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1198-1199
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• 2023

부동산 시장은 다양한 요인에 의해 가격이 결정되며 거시경제 변수뿐 만 아니라 뉴스 기사, SNS 등 다양한 비정형 데이터의 영향을 받는다. 특히 뉴스 기사는 국민들이 느끼는 경제 심리를 반영하고 있어 부동산 가격에 영향을 크게 미치는 변수라고 판단된다. 본 연구에서는 뉴스 기사의 세분화된 감정 분석을 통해 전통적인 분석 방법보다 더 의미 있는 결과를 얻을 수 있는 부동산 가격 예측 모델을 생성하였으며 뉴스 기사로부터 심리 지수를 산출하기 위해 생성 AI 를 활용하였다. 제안하는 매매가격지수 예측 모델을 통해 부동산 시장과 뉴스 기사와의 관계성에 대해 파악할 수 있으며, 사회/경제적 동향을 반영한 부동산 가격 변동을 예측할 수 있을 것으로 보인다.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.203-217
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• 2018

The research objective of this study is to analyze the aspects of small group decision-making process based on reading news reports in the context of the socio-scientific issues (SSI) activity related to climate change. Twenty-two high school students from Gyeonggi Province, South Korea, were asked to read two news reports on the UN climate change conferences and take a stance on joining the Paris Agreement both as an individual and as a small group. The news reports were analyzed in terms of genre, discourse, and style adapting the critical discourse analysis (CDA) and the decision-making processes of the small groups were examined on recognizing a problem and evaluating alternatives and decisions. The results from analyzing the news reports denoted that the Paris agreement is not only related to finding ideal solutions to climate change, but rather, connected to political or economic interests and power relationship. In the stage of recognizing a problem, meanwhile, different frames which students recognize the Paris agreement and discourses in the foreground of the news reports were the critical causes in terms of identifying the problem. In the stage of evaluating alternatives and decisions, the equity and fairness were the criteria for the small group discussions. This study implies the necessity of the scientific literacy instruction to develop the ability to critical reading in the context of the SSI.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.85-94
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• 2013

With the emergence of world wide web, in particular web 2.0 the rapidly growing amount of news articles has created a problem for users in selection of news articles according to their requirements. To overcome this problem different clustering mechanism has been proposed to broadly categorize news articles. However these techniques are totally machine oriented techniques and lack users' participation in the process of decision making for membership of clustering. In order to overcome the issue of zero-participation in the process of clustering news articles in this paper we have proposed a framework for clustering news articles by combining users' judgments that they post on twitter with the news articles to cluster the objects. We have employed twitter hash-tags for this purpose. Furthermore we have computed the credibility of users' based on frequency of retweets for their tweets in order to enhance the accuracy of the clustering membership function. In order to test performance of proposed methodology, we performed experiments on tweets messages tweeted during general election 2013 in Pakistan. Our results proved over claim that using users' output better outcome can be achieved then ordinary clustering algorithms.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.197-199
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• 2015

장기간 선박이라는 공간에서 생활하면서 이가정성과 이사회성 등의 특성을 갖는 외항상선해기사들이 이직을 고려할 때 어떤 요인으로 의사결정하게 되는지에 대하여 AHP기법을 이용하여 분석하고, 이직율을 낮출 수 있는 대안을 모색하였다.

• Annual Conference on Human and Language Technology
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• 2013.10a
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• pp.107-109
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• 2013

주식 시장에서 거래되고 있는 증권은 MACD(Moving Average Convergence Divergence), Stochastic 등의 보조 지표를 이용하는 기술적 분석을 통하여 매수/매도 시점을 결정한다. 주식 시장의 객관적인 자료를 통하여 분석하는 기술적 분석 방법은 주식 시장 외적인 요소를 반영하는데 있어 한계점이 존재한다. 본 논문에서는 기술적 분석 방법에 기사를 종목별로 분류하고 기사의 긍정 및 부정을 판별하는 문서 분류 기법을 적용하여 주식 외적인 요소를 반영하는 시스템을 제안한다.

• Smart Media Journal
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• v.6 no.1
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• pp.47-53
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• 2017

Social issues are important factors that decide government policy and newspapers are critical channels that reflect them. Analysing news articles can contribute to understanding social issues, but it is very difficult to analyse the unstructured large volumes of news data manually. Therefore, this study aims to analyze the different views among stakeholders of a specific social issue by using text analysis, word cloud analysis and associative analysis methods, which systematically transform unstructured news data into structured one. We analyzed a total of 115 news articles and a total of 6,772 comments, collected from the selected newspapers (Chosun-Il-bo, Joongang-Il-bo, Donga-Il-bo, Maeil Newspaper, Busan-Il-bo) for two weeks. We found that there are significant differences in tone between newspapers. While nation-wide daily newspapers focus on political relations with local areas, local daily newspapers tend to write articles to represent local governments' interests.