• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.148-158
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• 2009

Recently, media contents are moving frequently between different media. TV, film, musical or animation, adapt killer story to each other. This tends to develop the new possibility of distribution of media contents. This study will analyse the trend of content industry. Particularly, we will focus on TV dramas, films and musicals : 61 samples have been extracted by Naver website. As a result, remakes have been increased since 2006. TV dramas and films have been used the most for source genres. Particularly, the story of films have been transferred for almost every genres including musicals.

• The Journal of Bigdata
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• v.4 no.2
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• pp.185-194
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• 2019

In the 100-year history of Korean films, Korean films have grown to more than 100 million viewers every year since 2012, and their total sales are estimated at 1 trillion. It is assumed that the influence on the popularity of Korean movies is related to 2012, when 60% of smartphone penetration rate and 30 million subscribers exceeded. As a result, before and after 2012, changes in movie boxing factor variables were needed, and the prediction model trained as a new independent variable was applied to actual data.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.9
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• pp.1069-1084
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• 2011

This study investigates the main trend of LOHAS, examines and analyzes the LOHAS marketing cases of the fashion industry, and proposes an effective LOHAS marketing strategy for the domestic fashion market. Data were collected from Naver, Google and Daum from 2005 (when LOHAS began to be recognized) to October $31^{st}$ 2010. We searched the research material with keywords related to the research subject (such as eco, green, well being, echo-friendly, LOHAS, sustainable, environmental management, and green management) to conduct a theoretical and exploratory study through qualitative analysis. The data are analyzed with three types such as personal value of eco-friendly fabric, economical value of recycled fabric and re-use or re-form, and social-ethical value of distribution and promotion. The research results show that LOHAS marketing activities focused on personal values and social-ethical values (rather than economical value) and from an eco-friendly management centered on merchandise; in addition, an eco-friendly supply chain management incorporated with a management system were applied. LOHAS marketing strategies at home and abroad revealed some differences in the cases of eco-friendly fabric, recycling, and fair trade.

• The Journal of Economics, Marketing and Management
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• v.9 no.1
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• pp.1-14
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• 2021

Purpose: The article deals with the proposition that consumers' fashion consumption behavior will still follow the consumption behavior of fast fashion, despite recognizing the importance of slow fashion. Research design, data and methodology: The research model to verify this proposition is topic modelling with big data including unstructured textual data. we combined 5,506 news articles posted on Naver news search platform during the 2003-2019 period about fast fashion and slow fashion, high-frequency words have been derived, and topics have been found using LDA model. Based on these, we examined consumers' perception and consumption behavior on slow fashion through the analysis of Topic Network. Results: (1) Looking at the status of annual article collection, consumers' interest in slow fashion mainly began in 2005 and showed a steady increase up to 2019. (2) Term Frequency analysis showed that the keywords for slow fashion are the lowest, with consumers' consumption patterns continuing around 'brand.' (3) Each topic's weight in articles showed that 'social value' - which includes slow fashion - ranked sixth among the 9 topics, low linkage with other topics. (4) Lastly, 'brand' and 'fashion trend' were key topics, and the topic 'social value' accounted for a low proportion. Conclusion: Slow fashion was not a considerable factor of consumption behavior. Consumption patterns in fashion sector are still dominated by general consumption patterns centered on brands and fast fashion.

• 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.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.166-171
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• 2024

Recently, there has been an increasing trend in the role of social media in tourism marketing. We analyze changes in tourism marketing trends using tourism marketing keywords through social media networks. The aim is to understand marketing trends based on the analyzed data and effectively create, maintain, and manage customers, as well as efficiently supply tourism products. Data was collected using web data from platforms such as Naver, Google, and Daum through TexTom. The data collection period was set for one year, from December 1, 2022, to December 1, 2023. The collected data, after undergoing refinement, was analyzed as keyword networks based on frequency analysis results. Network visualization and CONCOR analysis were conducted using the Ucinet program. The top words in frequency were 'tourists,' 'promotion,' 'travel,' and 'research.' Clusters were categorized into four: tourism field, tourism products, marketing, and motivation for visits. Through this, it was confirmed that tourism marketing is being conducted in various tourism sectors such as MICE, medical tourism, and conventions. Utilizing digital marketing via online platforms, tourism products are promoted to tourists, and unique tourism products are developed to increase city branding and tourism demand through integrated tourism content. We identify trends in tourism marketing, providing tourists with a positive image and contributing to the activation of local tourism.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.108-113
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• 2024

The purpose of this study is to analyze user perceptions of tourism platforms through big data. Data were collected from Naver, Daum, and Google as big data analysis channels. Using semantic network analysis with the keyword 'tourism platform,' a total of 29,265 words were collected. The collection period was set for two years, from August 31, 2021, to August 31, 2023. Keywords were analyzed for connected networks using TexTom and Ucinet programs for social network analysis. Keywords perceived by tourism platform users include 'travel,' 'diverse,' 'online,' 'service,' 'tourists,' 'reservation,' 'provision,' and 'region.' CONCOR analysis revealed four groups: 'platform information,' 'tourism information and products,' 'activation strategies for tourism platforms,' and 'tourism destination market.' This study aims to expand and activate services that meet the needs and preferences of users in the tourism field, as well as platforms tailored to the changing market, based on user perception, current status, and trend data on tourism platforms.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.14-28
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• 2015

Numerous research has been conducted using internet search data since the mid-2000s. For example, Google Inc. developed a service predicting influenza patterns using the internet search data. The main objective of this study is to prove the hypothesis that highway traffic indices are similar to the internet search patterns. In order to achieve this objective, a model to predict the number of vehicles entering the expressway and space-mean speed was developed and the goodness-of-fit of the model was assessed. The results revealed several findings. First, it was shown that the Google search traffic was a good predictor for the TCS entering traffic volume model at sites with frequent commute trips, and it had a negative correlation with the TCS entering traffic volume. Second, the Naver search traffic was utilized for the TCS entering traffic volume model at sites with numerous recreational trips, and it was positively correlated with the TCS entering traffic volume. Third, it was uncovered that the VDS speed had a negative relationship with the search traffic on the time series diagram. Lastly, it was concluded that the transfer function noise time series model showed the better goodness-of-fit compared to the other time series model. It is expected that "Big Data" from the internet search data can be extensively applied in the transportation field if the sources of search traffic, time difference and aggregation units are explored in the follow-up studies.

• The Journal of the Korea Contents Association
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• v.15 no.1
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• pp.357-365
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• 2015

Folk medicine is traditionally passed down to cure disease, and adverse events (AEs) of folk medicine are any unfavorable and unintended discomforts temporally associated with the use of folk medicine. The aim of this study was to analyze AEs types and risks of folk medicine through the internet news articles. Included in this analysis are all articles on the topic of folk medicine and AE reported in the top 3 online news websites (NAVER, DAUM and NATE) determined by InternetTrend$^{TM}$(www.internettrend.co.kr). It was searched in the last five years (between 1 January 2009 and 28 February 2014). In total, 18 AEs articles of 973 news articles met our inclusion criteria. A total of 27 people were experienced AEs associated with use of folk medicine. Age was from 4 months to 76 years old, and it was occurred in both men and women. Folk medicine that caused AEs in twice or more was therapy that patient taking the dictamnus or aconitum of toxic herbal medicines, vinegar therapy of external use to topical skin, and cupping or bee sting therapy by practitioners. Death as a kind of serious AEs was 11 people, and 10 people were died after treatment by unqualified practitioner. Folk medicine that is popular and widely used in Korea is actively interacted with information on the internet, so it apt to misuse and abuse without guidance of health professionals. Aspects of health care system, we point out that the need for government and medical society establish not only correct health information plan and promotion of risk but also system as reporting and monitoring of AEs by folk medicine.

• Journal of Society of Occupational Therapy for the Aged and Dementia
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• v.12 no.2
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• pp.67-74
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• 2018

Objective : The purpose of this study is to quantitatively analyze the role of occupational therapy in long - term care insurance for the elderly using text mining, one of the big data analysis techniques. Method : For the analysis of newspaper articles, "Long - Term Care Insurance for the Elderly + Occupational Therapy for the Elderly" was collected after the period from 2007 to 208. Naver, which has a high share of the domestic search engine, utilized the database of Naver News by utilizing Textom, a web crawling tool. After collecting the article title and original text of 510 news data from the collection of the elderly long term care insurance + occupational therapy search, we analyzed the article frequency and key words by year. Result : In terms of the frequency of articles published by year, the number of articles published in 2015 and 2017 was the highest with 70 articles (13.7%), and the top 10 terms of the key word analysis showed the highest frequency of 'dementia' (344) In terms of key words, dementia, treatment, hospital, health, service, rehabilitation, facilities, institution, grade, elderly, professional, salary, industrial complex and people are related. Conclusion : In this study, it is meaningful that the textual mining technique was used to more objectively confirm the social needs and the role of the occupational therapist for the dementia and rehabilitation in the related key keywords based on the media reporting trend of the elderly long - term care insurance for 11 years. Based on the results of this study, future research should expand research field and period and supplement the research methodology through various analysis methods according to the year.