• Journal of Industrial Convergence
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• v.17 no.4
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• pp.33-38
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• 2019

Regional tourism is an effective means of revitalizing the local economy and improving the image of the region. In order to revitalize this, efforts should be made to create regionally specialized tourism products and to preserve the unique culture and traditions. Among them, gathering information about visitors and securing the quality competitiveness of the contents of tourism contents are very important to increase the potential of cultural tourism festival. This paper collects, refines, and processes the festival-related data in a specific area in order to enhance the visitor's tourism needs and satisfaction. In particular, negative words and positive words raised during the festival were analyzed through big data visualization using word cloud.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.33-46
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• 2021

Using news big data analysis, this study was aimed to examine the suicide phenomena in Korean society, and to evaluate whether suicide prevention policies reflect social phenomena appropriately. For this purpose, 9,142 news titles with suicide as the keyword were collected from eight central newspapers between 2000 to 2018. Nouns were extracted, and data was refined for network analysis. The total period was divided into 4 periods based on the 1st and 2nd suicide prevention policies, and the characteristics of suicide phenomena in each period were identified through the top 50 frequent main words and the clusters. As a result, period 1 (2000~2003) with 6 clusters (military, internet environment, economic problems, pessimism, school, corruption), period 2 (2004~2008) with 8 clusters (high social class, school, economic problems, suicide attempts, family issues, social problems, military, responsibilities), period 3 (2009~2013) with 6 clusters (school, family issues, suicide attempts, occupation, military, investigation), and period 4 (2014~2018) with 8 clusters (military, suicide insurance money, family issues, suicide attempts, occupation, job stress, celebrity, corruption) were identified. Study results suggested the characteristics of suicide phenomena in our society. Further, the appropriateness of the implementation of suicide prevention policies was discussed.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.105-112
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• 2020

The present study aims to explore news sharers' characteristic. Specifically, it aims to look at news sharers' demographic characteristics, old media news usage and new media news usage. Besides, it also explores factors affecting news sharing behavior. The study used the second data of Korea Press Foundation. Findings from surveys suggest that first, news sharers are younger and have higher education than not news sharers. Second, news sharers use less news through old media while more news through new media. Third, political orientation, portal, SNS and online video platform new usage, messenger news reliability have positive effects on news sharing, while age and portal news reliability have negative effects on it. Based on these findings, implication, limitations, and topics for future research are discussed.

• Knowledge Management Research
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• v.22 no.2
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• pp.1-17
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• 2021

In this study, we predicted the bitcoin prices of Bithum and Coinbase, a leading exchange in Korea and USA, using ARIMA and Recurrent Neural Networks(RNNs). And we used news articles from each country to suggest a separated RNN model. The suggested model identifies the datasets based on the changing trend of prices in the training data, and then applies time series prediction technique(RNNs) to create multiple models. Then we used daily news data to create a term-based dictionary for each trend change point. We explored trend change points in the test data using the daily news keyword data of testset and term-based dictionary, and apply a matching model to produce prediction results. With this approach we obtained higher accuracy than the model which predicted price by applying just time series prediction technique. This study presents that the limitations of the time series prediction techniques could be overcome by exploring trend change points using news data and various time series prediction techniques with text mining techniques could be applied to improve the performance of the model in the further research.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.2
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• pp.159-178
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• 2019

The purpose of the study is to examine the trend in the change of relation between countries (Czech and Korea) through analysis of portal new articles. In order to achieve the purpose, we analyzed news articles about Czech from 1990 to March 31st, 2019. We divided it into 6 periods by every 5 years, reviewed 200 news articles for each period totaling 1,200 news articles, and categorized them into 4 categories by subject (politics, economy, society and culture, and educations). The result of the study showed the subject of society and culture represented the largest proportion of all news articles. We also found that the range of changes in the sub-categories of society and culture occurred most extensively. We concluded the paper with several suggestions that could promote cooperation between Korea and Czech.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.17-20
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• 2018

대중의 관심인 공공이슈를 파악하기 위하여 다양한 종류의 빅데이터를 분석하는 연구가 진행되고 있다. 그러나 기존의 연구에서는 키워드의 노출 횟수만 파악하여 결과로 반영한다. 본 논문은 포털 사이트로부터 얻은 언론사별 뉴스 빅데이터를 이용하여 키워드별 노출 빈도수, 댓글 수 및 추천 수를 반영한 분석 방법을 제안하였다. 공공이슈를 추출하여 얻어낸 키워드들을 워드클라우드, Sankey다이어그램과 같은 형태로 시각화하여 사용자에게 제공한다. 제안된 방법을 사용하면 대중의 반응을 반영한 분석 결과를 확인 할 수 있다.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.223-228
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• 2020

The stock price reflects people's psychology, and factors affecting the entire stock market include economic growth rate, economic rate, interest rate, trade balance, exchange rate, and currency. The domestic stock market is heavily influenced by the stock index of the United States and neighboring countries on the previous day, and the representative stock indexes are the Dow index, NASDAQ, and S & P500. Recently, research on stock price analysis using stock news has been actively conducted, and research is underway to predict the future based on past time series data through artificial intelligence-based analysis. However, even if the stock market is hit for a short period of time by the forecasting system, the market will no longer move according to the short-term strategy, and it will have to change anew. Therefore, this model monitored Samsung Electronics' stock data and news information through text mining, and presented a predictable model by showing the analyzed results.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.317-325
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• 2018

With the aim of creating new economic values and strengthening national competitiveness, governments and major private companies around the world are continuing their interest in big data and making bold investments. In order to collect objective data, such as news, securing data integrity and quality should be a prerequisite. For researchers or practitioners who wish to make decisions or trend analyses based on objective and massive data, such as portal news, the problem of using the existing Crawler method is that data collection itself is blocked. In this study, we implemented a method of collecting web data by addressing existing crawler-style problems using the cloud service platform provided by Amazon Web Services (AWS). In addition, we collected 'gas safety' articles and analyzed issues related to gas safety. In order to ensure gas safety, the research confirmed that strategies for gas safety should be established and systematically operated based on five categories: accident/occurrence, prevention, maintenance/management, government/policy and target.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.412-415
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• 2018

헌재, 대부분의 여론조사는 전통적 여론 조사 방식을 사용하고 있다. 그러나 이 방식은 온라인 상에서의 여론을 반영하지 못한다는 문제점이 존재한다. 따라서 이를 해결하고 온라인 상에서의 여론을 반영하기 위해, 비정형 뉴스 데이터를 이용한 지지율 분석 방안을 제안하고자 한다. 이 연구에서는 제안 방안을 알아보고 기존의 방식과 비교한 장단점, 시사점, 개선방안 등을 알아봄으로써 새로운 여론조사 방식의 제안을 목적으로 한다.

• Journal of the Korean Society for information Management
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• v.36 no.3
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• pp.7-36
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• 2019

In this study, quantitative and content analysis was conducted on 37,818 news articles that were reported on the subject of 'library' for 29 years from 1990 to 2018 in order to analyze the tendency of media coverage about 'library'. First, the quantitative change in media coverage was analyzed according to the criteria by time, subject and media type. In addition, keyword frequency analysis and semantic network analysis were conducted to analyze the trends of the contents of the press and the frames inherent in the press. The results showed that the media showed a major interest in the library's informational, educational, and cultural functions, and the trend of the subject's interest was generally consistent with that of the library community, except for the issue of librarianship. Lastly, the main attitudes that the media take toward the reporting of library articles were the reporting and advertising functions.