• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.143-146
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• 2008

This study aimed to suggest the way to support flood disaster older survivors with analysing how relief services and their human resources are used. For this study, the data was collected from 184 elderly aged over 65 years from Inje and Pyungchang in Gangwon province where lots of flood damages were done. The results of the study was elderly used human resources of public servant/military soldiers, volunteers as public or official services than as private resources. These results provide the evidence that public or official human resources are very helpful to control their emergency situations because there is hardly any use of their private human resources except for assistance from their family. And it shows that older people are willing to use services of life rescue and information services of their family members safety rather than basic supplies, medical care or medicine providing. With this findings we suggest informing the news of family safety including basic necessaries are highly signigicant. Thus, it is useful for disaster planners to understand building immediate life rescue and accurate information delivery systems. These are relevant to older adults' psychological well-being, thus, providing news of family safety including offering material resources are highly needed for older disaster survivors.

• Journal of Preventive Medicine and Public Health
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• v.52 no.6
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• pp.384-392
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• 2019

Objectives: This study aimed to explore the health inequality discourse in the Korean press by analyzing newspaper articles using a relatively new content analysis technique. Methods: This study used the search term "health inequality" to collect articles containing that term that were published between 2000 and 2018. The collected articles went through pre-processing and topic modeling, and the contents and temporal trends of the extracted topics were analyzed. Results: A total of 1038 articles were identified, and 5 topics were extracted. As the number of studies on health inequality has increased over the past 2 decades, so too has the number of news articles regarding health inequality. The extracted topics were public health policies, social inequalities in health, inequality as a social problem, healthcare policies, and regional health gaps. The total number of occurrences of each topic increased every year, and the trend observed for each theme was influenced by events related to its contents, such as elections. Finally, the frequency of appearance of each topic differed depending on the type of news source. Conclusions: The results of this study can be used as preliminary data for future attempts to address health inequality in Korea. To make addressing health inequality part of the public agenda, the media's perspective and discourse regarding health inequality should be monitored to facilitate further strategic action.

• Journal of Contemporary Eastern Asia
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• v.20 no.2
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• pp.108-128
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• 2021

Research on the news coverage of North Korea has been paying less attention to social media platforms than to legacy media. An increasing number of social media users post, retweet, share, interpret, and set agendas on North Korea. The accessibility of international users and North Korea's publicity purposes make social media a venue for expression, news diversity, and framing about the nation. This study examined the sentiment of Twitter posts on North Korea from a framing perspective and the relationship between network strengths and sentiment from a social network perspective. Data were collected using two tools: Jupyter Notebook with Python 3.6 for preliminary analysis and NodeXL for main analysis. A total of 11,957 tweets, 10,000 of which were collected using Python and 1,957 tweets using NodeXL, about North Korea between June 20-21, 2020 were collected. Results demonstrated that there was more negative sentiment than positive sentiment about North Korea in the sampled Twitter posts. Some users belonging to small network sizes reached out to others on Twitter to build networks and spread positive information about North Korea. Influential users tended to be impartial to sentiment about North Korea, while some Twitter users with a small network exhibited high percentages of positive words about North Korea. Overall, marginalized populations with network bonding were more likely to express positive sentiment about North Korea than were influencers at the center of networks.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.143-154
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• 2021

This study aims to explore the dynamic conditional correlation (DCC) between ten Asian stock indexes, the US stock index, and Bitcoin by using the dynamic conditional correlation model. The time span of the daily data is between January 2015 to May 2021, the total observation is 1,116. DCC(1,1)-EGARCH(1,1) with multivariate t and normal distributions for the DCC and EGARCH models, respectively, outperforms other models by the goodness of fit values. Except for Bitcoin, we discovered that the majority of the securities' volatilities have a very high volatility persistence. Furthermore, the negative shocks/news have more impact on the volatilities than positive shocks/news in most of the cases, except the stock index of China and Bitcoin. Most of the correlation pairs exhibit higher correlation during the COVID-19 pandemic compared to the pre-COVID-19, except Hong Kong-The US and Malaysia-Indonesia. Moreover, the correlation between Asian stock indexes during the COVID-19 pandemic is statistically higher than the pre-COVID-19 pandemic. However, there are a few instances where the Hong Kong stock index and a few countries are identical. The result of correlation size shows the connectedness between Asian stock markets, which are well-connected within the region, especially with South Korea, Singapore, and Hong Kong.

• Korean Linguistics
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• v.72
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• pp.199-225
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• 2016

This study has two main purposes: to establish a list of source domains in the metaphors for Middle East respiratory syndrome (MERS) and to uncover ideological meanings embedded in them in Korean news reports from KBS and JTBC. The first part of this study presents metaphors such as [MERS IS WAR], [MERS IS WAVE], [MERS IS A LIVING THING], and [MERS IS A THING], which were found in the data. The latter part of this study deals with how the two broadcasting companies use these metaphors differently according to their ideologies. In the metaphor of [MERS IS WAR], KBS tends to show less of the agents who controls the war since the war against MERS has failed which casts responsibility to the controlling agents, the government and big hospitals. In this, KBS tries to present less of the information of the responsible agents that presented in JTBC. Through the metaphor of [MERS IS WAVE], KBS presents the aftermath of MERS as something not serious. Compared to JTBC, KBS tends to suggest that the aftermath of MERS is predominantly an economic effects by metaphorically suggesting that predominantly the economic sector got hit by MERS.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.153-171
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• 2019

Competition among cities has become fierce with decentralization and globalization, and each city tries to establish a brand image of the city to build its competitiveness and implement its policies based on it. At this time, surveys, expert interviews, etc. are commonly used to establish city brands. These methods are difficult to establish as sampling methods an empirical component, the biggest component of a city brand. In this paper, therefore, based on the precedent research's urban brand measurement and components, the words representing each city image property were extracted and relocated to five indicators to form the evaluation index. The constructed indicators have been validated through the review of three experts. Through the index, we analyzed the brands of four cities, Ulsan, Incheon, Yeosu, and Gyeongju, and identified the factors by using Topic Modeling and Word Cloud. This methodology is expected to reduce costs and monitor timely in identifying and analyzing urban brand images in the future.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.448-459
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• 2021

In this paper, we propose a method of predicting the next-day stock price fluctuations of 10 KOSDAQ-listed companies in 5G, autonomous driving, and electricity sectors by training SVM, XGBoost, and LightGBM models from macroeconomic·financial market indicators, technical indicators, social interest indicators, and daily positive indices extracted from online news. In the three experiments to find out the usefulness of social interest indicators and daily positive indices, the average accuracy improved when each indicator and index was added to the models. In addition, when feature selection was performed to analyze the superiority of the extracted features, the average importance ranking of the social interest indicator and daily positive index was 5.45 and 1.08, respectively, it showed higher importance than the macroeconomic financial market indicators and technical indicators. With the results of these experiments, we confirmed the effectiveness of the social interest indicators as alternative data and the daily positive index for predicting stock price fluctuation.

• Journal of Industrial Convergence
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• v.17 no.3
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• pp.17-22
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• 2019

As the value of big data is recognized as important, it is possible to advance decision making by effectively introducing and improving the development and utilization of JAVA and R programs that can analyze vast amounts of existing and unstructured data to governments, public institutions and private businesses. In this study, news data was collated and analyzed through text mining techniques in order to establish marketing strategies based on consumers' airline preferences. This research is meaningful in establishing marketing strategies based on analysis results by analyzing consumers' airline preferences using high-level big data utilization program techniques for data that were difficult to obtain in the past.

• Convergence Security Journal
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• v.18 no.1
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• pp.103-110
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• 2018

Modern society is increasingly demanding in many areas of big data processing technology to collect, aggregate, and analyze large amounts of data over the Internet and SNS. A typical application is to evaluate the reputation of a company or college. To measure and quantify a reputation, fair and precise data and efficient data processing are very important. For this purpose, a quantitative quotient was obtained using public data, a qualitative quotient was obtained through sentiment analysis using news articles, and a complex college reputation quotient was calculated. In this paper, a complex college reputation quotient was calculated based on the quantitative index, reflecting the sentimental reputation, and based on the proposed mixed university system. In this paper, the Complex College Reputation System(CCRS) was proposed, which produced the Complex College Reputation Quotient with an objective quantitative quotient and qualitative quotient reflecting the sentimental reputation to measure the college reputation.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.353-360
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• 2023

This paper explores notable shifts in the restaurant startup market following the lifting of social distancing measures. Key trends identified include an escalated interest in startups, a heightened focus on the quality and diversity of food, a relative decline in the importance of delivery services, and a growing interest in specific industry sectors. The study's data collection spanned three years, from April 2021 to May 2023, encompassing the period before and after social distancing. Data were sourced from a range of online platforms, including blogs, news sites, cafes, web documents, and intellectual forums, provided by Naver, Daum, and Google. From this collected data, the top 50 words were identified through a refinement process. The analysis was structured around the social distancing application period, comparing data from April 2021 to April 2022 with data from May 2022 to May 2023. These observed trend changes provide founders with valuable insights to seize new market opportunities and formulate effective startup strategies. In summary, We offer crucial insights for founders, enabling them to comprehend the evolving dynamics in food service startups and to adapt their strategies to the current market environment.