• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2022년도 제65차 동계학술대회논문집 30권1호
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• pp.237-238
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• 2022

본 연구에서는 언택트 시대에 여행 트렌드가 된 차박을 위한 모바일 앱 'GO차박'을 설계하고 구현하였다. 코로나 19로 인해 언택트 문화가 새로운 트렌드로 자리 잡게 되면서 '차박'에 대한 관심이 급격하게 증가하게 되었다. 이에 따라 차박에 대한 정보를 찾는 수요자와 정보는 증가하였으나 방대한 정보에 대한 용이한 접근을 제공하고 증가하는 수요자를 만족시킬 수 있는 어플리케이션은 미흡하였다. 따라서 본 연구에서는 많은 차박 수요자들에게 쉽게 접근하여 차박에 대한 정보를 종합적이고 간편하게 찾아볼 수 있고 서로 정보 공유도 할 수 있는 모바일 앱을 제공하고자 'GO차박'을 개발하게 되었다. 방대한 정보를 다루기 때문에 깔끔한 UI를 구성하였고 Firebase와 NaverSearch API, Naver Map API, OpenWeatherAPI를 사용하여 정보의 정확도를 높이고자 하였다. 본문에서는 차박 앱에 대한 주요 기능들을 설명하고 결론에서는 'GO차박'의 기대 효과와 향후 확장 방향에 대해 제시하고 있다.

• 인간식물환경학회지
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• 제24권6호
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• pp.563-572
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• 2021

Background and objective: The ongoing COVID-19 pandemic restricted daily life, forcing people to spend time indoors. With the growing interest in mental health issues and residential environments, 'pet plants' have been receiving attention during the unprecedented social distancing measures. This study aims to analyze the change in trends of pet plants before and during the COVID-19 pandemic and provide basic data for studies related to pet plants and directions of future development. Methods: A total of 2,016 news articles using the keyword 'pet plants' were collected on Naver News from January 1, 2018 to August 15, 2019 (609 articles) and January 1, 2020 to August 15, 2021 (1,407 articles). The texts were tokenized into words using KoNLPy package, ultimately coming up with 63,597 words. The analyses included frequency of keywords and topic modeling based on Latent Dirichlet Allocation (LDA) to identify the inherent meanings of related words and each topic. Results: Topic modeling generated three topics in each period (before and during the COVID-19), and the results showed that pet plants in daily life have become the object of 'emotional support' and 'healing' during social distancing. In particular, pet plants, which had been distributed as a solution to prevent solitary deaths and depression among seniors living alone, are now expanded to help resolve the social isolation of the general public suffering from COVID-19. The new term 'plant butler' became a new trend, and there was a change in the trend in which people shared their hobbies and information about pet plants and communicated with others in online. Conclusion: Based on these findings, the trend data of pet plants before and after the outbreak of COVID-19 can provide the basis for activating research on pet plants and setting the direction for development of related industries considering the continuous popularity and trend of indoor gardening and green hobby.

• 한국의류산업학회지
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• 제22권5호
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• pp.639-649
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• 2020

This study investigates consumer opinions of clothing care and provides fundamental data to decision-making for oncoming development of clothing care system. Textom, a web-matrix program, was used to analyze big data collected from Naver and Daum with a keyword of "clothing care" from March 2019 to February 2020. A total of 22, 187 texts were shown from the big data collection. Collected big data were analyzed using text-mining, network, and CONCOR analysis. The results of this study were as follows. First, many keywords related to clothing care were shown from the result of frequency analysis such as style, Dryer, LG Electronics, Product, Customer, Clothing, and Styler. Consumers were well recognizing and having an interest in recent information related to the clothing care system. Second, various keywords such as product, function, brand, and performance, were linked to each other which were fundamentally related to the clothing care. The interest in products of the clothing care system were linked to product brands that were also naturally linked to consumer interest. Third, the keywords in the network showed similar attributes from the result of CONCOR analysis that were classified into 4 groups such as the characteristics of purchase, product, performance, and interest. Lastly, positive emotions including goodwill, interest, and joy on the clothing care system were strongly expressed from the result of the sentimental analysis.

• 한국IT서비스학회지
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• 제15권2호
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• pp.81-92
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• 2016

Numerous people share their TV experience with other viewers on social media such as personal blogs and Twitter. It means that broadcast media, especially TV, affects the responses on social media. Moreover, the responses affect broadcast media ratings back. Social TV tried to use the relationship in marketing activities such as advertisement by analyzing the TV related social behavior. However, most of them used just the quantities of social media responses. This study analyzes the subjects of the responses on social media about specific TV dramas through topic modeling, and the relationship between the changes of popular topics and viewer ratings of the drama over specified periods. Five representative Korean dramas of 2014 were selected and Blog contents including viewer ratings about the dramas were collected from naver.com which is the representative portal in South Korea. The proposed analysis framework consists of three steps which are Blogs crawling, topic modeling, and topic trend analysis. We found some implications from the results of the topic trend analysis. Firstly, there were specific topics on dramas in social media. Secondly, the topics had some meaningful relationships with viewer ratings. Lastly, there were differences between the topics of dramas with higher viewer ratings and those with lower viewer ratings.

• 한국빅데이터학회지
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• 제3권1호
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• pp.63-71
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• 2018

최근 5년(2013~2017년) 연속 영화 총 관객 수가 2억 명이 넘는 국내 영화 산업에서 천만 관객을 돌파한 한국 영화 간에는 어떤 요인이 영향을 미쳤는지 분석해 보았다. 일반적으로 천만 관객 돌파에 영향을 주는 요인으로는 스크린 수와 평점을 중요하게 보는 시각이 많았다. 본 연구에서는 스크린 수, 평점을 포함하고 추가적으로 4가지 요인을 설정하여 가설을 수립하고 빅데이터 분석을 통해 천만 관객 돌파 유무와의 상관관계를 분석했다. 이를 통해 천만 관객 돌파 예측 정확도는 91%, 누적 관객 수 예측 정확도는 99.4%까지 맞추는 유의미한 결과를 얻었다.

• 디지털융복합연구
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• 제17권4호
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• pp.49-55
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• 2019

본 연구는 빅데이터 분석방법인 텍스트마이닝을 이용한 부동산시장 동향분석에 관한 연구로 자료는 2016년 8월부터 2017년 8월까지의 포털사이트인 네이버에 게시된 인터넷 뉴스를 통해 수집하였다. TF-IDF 분석결과, 주택, 분양, 가구, 시장, 지역 순으로 빈도가 높게 나타났고 대출, 정부, 대책, 규제 등 정책과 관련된 단어들도 많이 추출되었으며 지역관련 단어는 서울의 출현빈도가 가장 많은 것으로 나타났다. 지역과 관련된 단어 조합은 '서울-강남', '서울-수도권', '강남-재건축', '서울-재건축'의 출현빈도가 많은 것으로 나타나 강남지역 재건축에 대한 사람들의 관심과 기대가 높은 것을 알 수 있다.

• 아태비즈니스연구
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• 제12권2호
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• pp.161-174
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• 2021

Purpose - The purpose of this study was to examine the recent popular consumption trend, the hocance phenomenon, using social media big data. The study intended to present practical directions and marketing measures for the recovery and growth of the hotel industry after COVID-19 pandemic. Design/methodology/approach - Big data analysis has been used in various fields, and in this study, it was used to understand the hocance phenomenon. For three years from January 1, 2018 to December 31, 2020, we collected text data including the keyword 'hocance' from the blog and cafe of NAVER and Daum. TEXTOM and UCINET 6 were used to collect and analyze the data. Findings - According to the results of analysis, the words such as 'hocance', 'hotel', 'Seoul', 'travel', 'swimming pool', 'Incheon', 'breakfast', 'child' and 'friend' were identified with high frequency. The results of CONCOR analysis showed similar results in all three years. It has been confirmed that 'swimming pool', 'breakfast', 'child' and 'friend' are important when deciding on the hocance package. Research implications or Originality - The study was differentiated in that it used social media big data instead of traditional research methods. Furthermore, it reflected social phenomena as a consumption trend so there was practical value in establishing marketing strategies for the tourism and hotel industry.

• International Journal of Internet, Broadcasting and Communication
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• 제14권3호
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• pp.85-90
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• 2022

In this study, keywords from representative online portal sites such as NAVER, Google, and Youtube were collected based on text mining analysis technique using TEXTOM to check the changes in the restaurant industry before and after COVID-19. The collection keywords were selected as dining out, food service industry, and dining out culture. For the collected data, the top 30 words were derived, respectively, through the refinement process. In addition, comparative analysis was conducted by defining data from 2018 to 2019 before COVID-19, and from 2020 to 2021 after COVID-19. As a result, 8272 keywords before COVID-19 and 9654 keywords after COVID-19, a total of 17926 keywords, were derived. In order for the food service industry to develop after the COVID-19 pandemic, it is necessary to commercialize the recipes of restaurants to revitalize the distribution of home-use food products that replace home-cooked meals such as meal kits. Due to the social distancing caused by COVID-19, the dining out culture has changed and the trend has changed, and it has been confirmed that the consumption culture has changed to eating and delivering at home more safely than visiting restaurants. In addition, it has been confirmed that the consumption culture of existing consumers is changing to a trend of cooking at home rather than visiting restaurants.

• 패션비즈니스
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• 제26권3호
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• pp.138-154
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• 2022

The purpose of this study is to identify the characteristics of domestic American casual fashion trends using big data text mining analysis. 108,524 posts and 2,038,999 extracted keywords from Naver and Daum related to American casual fashion in the past 5 years were collected and refined by the Textom program, and frequency analysis, word cloud, N-gram, centrality analysis, and CONCOR analysis were performed. The frequency analysis, 'vintage', 'style', 'daily look', 'coordination', 'workwear', 'men's wear' appeared as the main keywords. The main nationality of the representative brands was Japanese, followed by American, Korean, and others. As a result of the CONCOR analysis, four clusters were derived: "general American casual trend", "vintage taste", "direct sales mania", and "American styling". This study results showed that Japanese American casual clothes are influenced by American casual clothes, and American casual fashion in Korea, which has been reinterpreted, is completed with various coordination and creative styles such as workwear, street, military, classic, etc., focusing on items and brands. Looks were worn and shared on social networks, and the existence of an active consumer group and market potential to obtain genuine products, ranging from second-hand transactions for limited edition vintages to individual transactions were also confirmed. The significance of this study is that it presented the characteristics of American casual fashion trends academically based on online text data that the public actually uses because it has been spread by the public.

• 한국의류산업학회지
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• 제25권1호
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• pp.72-81
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• 2023

As changes in social and economic paradigms are accelerating, and non-contact has become the new normal due to the COVID-19 pandemic, metaverse services that build societies in online activities and virtual reality are spreading rapidly. This study analyzes the perception and trend of metaverse fashion using big data. TEXTOM was used to extract metaverse and fashion-related words from Naver and Google and analyze their frequency and importance. Additionally, structural equivalence analysis based on the derived main words was conducted to identify the perception and trend of metaverse fashion. The following results were obtained: First, term frequency(TF) analysis revealed the most frequently appearing words were "metaverse," "fashion," "virtual," "brand," "platform," "digital," "world," "Zepeto," "company," and "game." After analyzing TF-inverse document frequency(TF-IDF), "virtual" was the most important, followed by "brand," "platform," "Zepeto," "digital," "world," "industry," "game," "fashion show," and "industry." "Metaverse" and "fashion" were found to have a high TF but low TF-IDF. Further, words such as "virtual," "brand," "platform," "Zepeto," and "digital" had a higher TF-IDF ranking than TF, indicating that they had high importance in the text. Second, convergence of iterated correlations analysis using UNICET revealed four clusters, classified as "virtual world," "metaverse distribution platform," "fashion contents technology investment," and "metaverse fashion week." Fashion brands are hosting virtual fashion shows and stores on metaverse platforms where the virtual and real worlds coexist, and investment in developing metaverse-related technologies is under way.