• Journal of Industrial Convergence
• /
• v.21 no.1
• /
• pp.167-173
• /
• 2023

As research has been published to predict future data using regression analysis or artificial intelligence as a method of analyzing economic indicators. In this study, we designed a system that predicts prospective futures prices using artificial intelligence that utilizes topic probability data obtained from past news articles using topic modeling. Topic probability distribution data for each news article were obtained using the Latent Dirichlet Allocation (LDA) method that can extract the topic of a document from past news articles via unsupervised learning. Further, the topic probability distribution data were used as the input for a Long Short-Term Memory (LSTM) network, a derivative of Recurrent Neural Networks (RNN) in artificial intelligence, in order to predict prospective futures prices. The method proposed in this study was able to predict the trend of futures prices. Later, this method will also be able to predict the trend of prices for derivative products like options. However, because statistical errors occurred for certain data; further research is required to improve accuracy.

• Journal of the Korea Society for Simulation
• /
• v.31 no.3
• /
• pp.35-44
• /
• 2022

In this study, we analyze and forecast quantum computer technology trends. Previous research has been mainly focused on application fields centered on technology for quantum computer technology trends analysis. Therefore, this paper analyzes important quantum computer technologies and performs future signal detection and prediction, for a more market driven technical analysis and prediction. As analyzing words used in news articles to identify rapidly changing market changes and public interest. This paper extends conference presentation of Cha & Chang (2022). The research is conducted by collecting domestic news articles from 2019 to 2021. First, we organize the main keywords through text mining. Next, we explore future quantum computer technologies through analysis of Term Frequency - Inverse Document Frequency(TF-IDF), Key Issue Map(KIM), and Key Emergence Map (KEM). Finally, the relationship between future technologies and supply and demand is identified through random forests, decision trees, and correlation analysis. As results of the study, the interest in artificial intelligence was the highest in frequency analysis, keyword diffusion and visibility analysis. In terms of cyber-security, the rate of mention in news articles is getting overwhelmingly higher than that of other technologies. Quantum communication, resistant cryptography, and augmented reality also showed a high rate of increase in interest. These results show that the expectation is high for applying trend technology in the market. The results of this study can be applied to identifying areas of interest in the quantum computer market and establishing a response system related to technology investment.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.5
• /
• pp.209-216
• /
• 2024

Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

• Journal of Digital Convergence
• /
• v.15 no.11
• /
• pp.85-95
• /
• 2017

The news media report the pledges of presidential candidates, which have important implications for political communication. This study is to investigate the difference between news coverage on the presidential candidate' s pledge and to discuss its implications. The sampled news from the two newspapers were analyzed for content analysis. Frequency analysis and Chi-square analysis are utilized with SPSS. As results, there was no difference in the tone of the article's headlines, but the difference of the tone between the article content was statistically significant. The results means that the media framing affect on the reader's perception. Follow - up study can be suggested a comparative study of past election candidates 'pledge reports, a network analysis for the news language, and a comparative analysis of newspaper coverage and broadcast coverage.

• Korean Journal of Social Welfare Studies
• /
• v.45 no.3
• /
• pp.97-125
• /
• 2014

The purpose of this study was to investigate the contributions and limitations of an independent internet newspaper dedicated to disability affairs. The materials analysed in this study were articles on personal assistance service conflicts between users and assistants by Ablenews. This study used inductive content analysis, responsibility frame analysis, and disability paradigm analysis. First, in general Ablenews appeared to report personal assistance service conflicts as they were. Second, the results showed that Ablenews tended to attribute the causes and solutions of the conflicts to the users and assistants. Third, nearly half of content units of Ablenews articles conveyed the perspective of rehabilitation paradigm though personal assisstanc services are closely related to independent living model. Based on the results this study suggested that Ablenews needs to improve specialty in reports on disability affairs using editorial staff, professional reporters, guests reporters with specialties.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.01a
• /
• pp.99-100
• /
• 2020

본 연구는 최근 우리나라 국민들의 주요 관심 교육정책인 '고교학점제' 관련 언론기사들을 한국언론재단의 빅카인즈(BIGKinds) 시스템을 활용하여 분석하였다. 본 연구에서는 2018년 1월 1일부터 2019년 11월 30일까지 기간을 설정한 후, 총 54개 언론사의 '고교학점제' 관련기사들을 추출하였다. 그 다음, 추출된 '고교학점제' 관련 기사들을 대상으로 뉴스트렌드 분석, 네트워크 지도 구현, 핵심어 추출 및 워드클라우드 제시 등의 연구과정을 거쳤다. 본 연구결과는 '고교학점제'의 정책 진행 과정성의 과제 및 쟁점들을 해결하는데 기초자료로 활용될 수 있을 것으로 기대된다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2023.07a
• /
• pp.331-332
• /
• 2023

최근 ChatGPT, 코딩교육, 디지털교과서 등의 새로운 용어와 산물들이 전국 단위 언론사를 통해, 교육 전문가(교사 등)와 일반 국민들에게 어떤 형태의 보도가 진행되는지 확인하는 것이 중요한 연구 출발점이다. 본 연구는 오늘날 학교교육, 교육방법(매체론) 등에 큰 변화를 줄 '인공지능'에 대한 전국 단위 언론사(일간지-11개사, 방송사-5개사)의 최근(2020-2023년) 보도형태를 분석하고 제시하였다. 본 연구에서는 2020년 1월부터 2023년 5월까지(3년 5개월간) 총 16개 언론사(일간지와 방송사)에서 보도한 '인공지능'와 '학교' 용어가 모두 포함된 관련 뉴스 기사들을 분석하였다. 분석대상 뉴스 빅데이터들을 대상으로 연도별 보도기사 건수 분석, 키워드 트렌드 분석, 연관어 분석(워드클라우드 제시) 등을 진행하였다.

• Journal of the Korean Society for information Management
• /
• v.24 no.2
• /
• pp.123-141
• /
• 2007

It has been known that predicting stock price is very difficult due to a large number of known and unknown factors and their interactions, which could influence the stock price. However, we started with a simple assumption that good news about a particular company will likely to influence its stock price to go up and vice versa. This assumption was verified to be correct by manually analyzing how the stock prices change after the relevant news stories were released. This means that we will be able to predict the stock price change to a certain degree if there is a reliable method to classify news stories as either favorable or unfavorable toward the company mentioned in the news. To classify a large number of news stories consistently and rapidly, we developed and evaluated a natural language processing based multi-stage news classification system, which categorizes news stories into either good or bad. The evaluation result was promising as the automatic classification led to better than chance prediction of the stock price change.

• Korean journal of communication and information
• /
• v.27
• /
• pp.63-91
• /
• 2004

The purpose of this study is to investigate the gender discourse of Korean newspapers. For this, the study analyzes the frames of frames of crime news on Chosun Daily and Hangyurae Newspaper for 2 years. The data are collected using KINDS, and include 265 crime articles involving woman. According to the results of this research, the episodic frames are used in the most of crime news. The five frame devices are founded in the episodic frame articles; the male subjectivity and the female objectivity, the male-oriented perspectives which reporters have, the abused sexual details and sensationalism, the emphasis of women body's fragility which imply woman's unavoidability as victims, and finally, blaming women who are victims of crimes. And in the articles of thematic frames, the similar frame devices are found. In particular, they only emphasize the problem of crime and fail to suggest a concrete resolution. Finally, the study discusses the findings relating to the patriarchal news making convention and the commercialism of newspaper industry. The two newspapers have been pursuing quite different political lines in Korean society. It is generally considered that Hangyurae newspaper is progressive and Chosun Daily is conservative. However, this study reveals that the way dealt with women in the crime news are not different. It is concluded that Korean newspapers still produce the gender discourse based on male-centric perspective and patriarchal ideology.

• Journal of Korea Society of Industrial Information Systems
• /
• v.25 no.6
• /
• pp.109-123
• /
• 2020

There has been a major change in the way of life and thinking of all mankind due to covid19. In particular, managerial issues related to supply chain such as global supply chain disruption, and trade friction among countries are drawing the attention. Accordingly, a number of studies are being conducted on the supply chain challenges and solutions to overcome the covid19 crisis, but published research on the impact of covid19 on supply chain management is lacking. In this study, network text analysis is conducted mainly on news articles and this study summarizes the issues related to supply chain management in the era of covid19. The trend analysis results indicated that actively discussed area was global supply chain restructuring and confirmed that main topics are re-shoring, applications of new technology, and the new normal in supply chains. The findings are expected to help expand the scope of research in supply chain management research in the covid19 era.