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Research on public sentiment of the post-corona new normal: Through social media (SNS) big data analysis (포스트 코로나 뉴노멀에 대한 대중감성 연구: 소셜미디어(SNS) 빅데이터 분석을 통해)

  • Ann, Myung-suk
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.2
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    • pp.209-215
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    • 2022
  • In this study, detailed factors of public sentiment toward the 'post-corona new normal' were examined through social media big data sentiment analysis. Thus, it is to provide basic data to preemptively cope with the post-COVID-19 era. For data collection and analysis, the emotional analysis program of 'Textom', a big data analysis program, was used. The data collection period is one year from October 5, 2020 to October 5, 2021, and the collection channels are set as blogs, cafes, Twitter, and Facebook on Daum and Naver. The original data edited and refined a total of 3,770 collected texts from this channel were used for this study. The conclusion is as follows. First, there is a high level of interest and liking for the 'post-corona new normal'. In other words, it can be seen that optimism such as daily recovery, technological growth, and expectations for a new future took the lead at 77.62%. Second, negative emotions such as sadness and rejection are 22.38% of the total, but the intensity of emotions is 23.91%, which is higher than the ratio, suggesting that these negative emotions are intense. This study has a contribution to the detailed factor analysis of the public's positive and negative emotions through big data analysis on the 'post-corona new normal'.

A study on the User Experience at Unmanned Checkout Counter Using Big Data Analysis (빅데이터 분석을 통한 무인계산대 사용자 경험에 관한 연구)

  • Kim, Ae-sook;Jung, Sun-mi;Ryu, Gi-hwan;Kim, Hee-young
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.2
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    • pp.343-348
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    • 2022
  • This study aims to analyze the user experience of unmanned checkout counters perceived by consumers using SNS big data. For this study, blogs, news, intellectuals, cafes, intellectuals (tips), and web documents were analyzed on Naver and Daum, and 'unmanned checkpoints' were used as keywords for data search. The data analysis period was selected as two years from January 1, 2020 to December 31, 2021. For data collection and analysis, frequency and matrix data were extracted through Textom, and network analysis and visualization analysis were conducted using the NetDraw function of the UCINET 6 program. As a result, the perception of the checkout counter was clustered into accessibility, usability, continuous use intention, and others according to the definition of consumers' experience factors. From a supplier's point of view, if unmanned checkpoints spread indiscriminately to solve the problem of raising the minimum wage and shortening working hours, a bigger employment problem will arise from a social point of view. In addition, institutionalization is needed to supply easy and convenient unmanned checkout counters for the elderly and younger generations, children, and foreigners who are not familiar with unmanned calculation.

Analysis of Use Behavior of Urban Park Users Expressing Depression on Social Media Using Text Mining Technique (텍스트 마이닝 기법을 활용한 SNS 상에서 우울감을 언급한 도시공원 이용자의 이용행태 분석)

  • Oh, Jiyeon;Nam, Seongwoo;Lee, Peter Sang-Hoon
    • The Journal of the Korea Contents Association
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    • v.22 no.6
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    • pp.319-328
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    • 2022
  • The purpose of this study was to investigate the relationship between depression due to the COVID-19 pandemic and park use behaviors using on line posts. During the period of the pandemic prevention activities, text data containing both 'park' and 'depression' were collected from blogs and cafes in the search engine of Naver and Daum, then analyzed using Text Mining and Social Network techniques. As a result, the main usage behaviors of park users who mentioned depression were 'look', 'stroll(walk)' and 'eat'. Other types of behaviors were connected centering around 'look', one of the communication behaviors. Also, from CONCOR analysis, as the cluster referred from communication behavior and dynamic behavior was formed as a single behavior type, it was considered park users with depression perceived the park as the space for communication and physical activities. As the spread of COVID-19 caused the restriction of communication activities, the users might consider parks as one of the solutions. In addition, it was considered that passive usage behaviors have prevailed rather than active ones due to the depression. Resulting outcomes would be useful to plan helpful urban park for citizens. It is necessary to further analyze the park use behavior of users in relation to the period of before/after the COVID-19 pandemic and the existence/nonexistence of depression.

A study on the expansion of culture industry and establishment of industrialization of well-dying education (웰다잉 교육의 문화산업 확산과 산업화 구축에 관한 연구)

  • Chang, Kyung-Hee;Kim, Moon-Joon;Kim, Seol-Hee;Park, Arma;Ahn, Sang-Yoon;Kim, Kwang-Hwan
    • Journal of Digital Convergence
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    • v.19 no.5
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    • pp.321-331
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    • 2021
  • The purpose of this study is to establish well-dying education, well-dying culture, and industrialization for well-aging. For this, data was collected through Gallup Korea from February 1, 2021 to February 22, 2021. As a result of the study, well-dying education experience was 4.7%, and education satisfaction was surveyed with 2.88 points out of 5. As a result of analyzing the needs of well-dying education according to the age groups, the educational demands of youth and middle-aged were in the order of hospice education and information, life-sustaining medical information, and funeral information. In the case of the young old, it was in the order of hospice education and information, funeral information, and psychological overcoming related to death. In the case of the elderly, the survey was conducted in the order of hospice education and information, funeral information, and life-care related information. The perception of industrialization related to the well-dying culture was inspected in the order of the well-dying café where you can talk about life and death, the well-dying experience such as the entrance experience, and the development of travel products related to culture and art (p<0.05). Such results can be usefully utilized in the development of well-dying education programs for well aging, cultural spreading, and industrialization.

Displacement of Early Business Entrants in a Gentrified Commercial Area: Survival Rates Compared to Those of Late Arrivers (상업젠트리피케이션에 따른 기존 상인의 이탈: 후기 진입 상인과의 생존율 변화 비교)

  • Cheon, SangHyun;Kim, Jieun
    • Land and Housing Review
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    • v.13 no.2
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    • pp.91-115
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    • 2022
  • This study examines changes in business survival rates in a gentrified commercial district by comparing early movers with late entrants. Using the Hongik University Commerical District, or Hongdae, as a case study, we adopt discrete-time survival analysis to compare survival rates between businesses established before 2000 (early movers) and ones established after 2000 (late arrivers). We compare the business survival patterns in a gentrified commercial district (experimental group) to non-gentrified commercial districts (control group) in Mapogu. We examine a survival-rate difference between early movers and late arrivers by different industrial categories. We finally examine a survival-rate gap between franchise and non-franchised businesses. The results show that the early movers have lower survival rates than the late arrivers in the gentrified Hongdae area, whereas there is no significant difference in survival rates between the early movers and the late arrivers in Mapogu. The early movers in daily-life-supporting businesses in Mapogu have even higher survival rates than the late-arrivers. In addition, franchised businesses have higher survival rates than non-franchised stores both in Hongdae and Mapogu. The results provide statistical and comprehensive evidence of the displacement of early movers at a more rapid pace in gentrified areas than non-gentrified aveas, which has been an anecdotal narrative.

A Metaverse-based Collaborative Content Building Model for Representative Libraries: Focusing on the Gyeonggi-do Region (광역대표도서관의 메타버스 기반 협력적 콘텐츠 구축 모델: 경기도 지역을 중심으로)

  • Seonghun Kim;Mi Ryung Kim;Yoon Ju Roh;Hyojung Sim
    • Journal of the Korean Society for information Management
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    • v.40 no.3
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    • pp.221-244
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    • 2023
  • Focusing on Gyeonggi Library, which is preparing Metaverse services using resident participatory budgets, we deduced the role of Metaverse suitable for metropolitan representative libraries, conducting a preliminary study and analyzing various informational resources. Subsequently, we presented a collaborative content construction and service model primarily centered around the metropolitan representative library. We conducted a survey targeting on-site librarians from metropolitan representative libraries, as well as various libraries across Gyeonggi Province and the entire nation. Through this survey, we extracted insights into the Metaverse role, content possibilities, and considerations for seamless cooperation within the scope of the metropolitan representative library. Based on the opinions of surveyed librarians, it was evident that the role of the metropolitan representative library's Metaverse should function as a tool for continuous utilization of library resources and serve as a space for the entire local community. Approximately three-fourths of the respondents expressed willingness to participate in collaborative content development. However, concerns were raised about human resource limitations, budget constraints, and excessive workloads as potential obstacles to participation. This highlighted the need for systematic support from the metropolitan representative library to address these concerns.

A Study on Deep Learning Model for Discrimination of Illegal Financial Advertisements on the Internet

  • Kil-Sang Yoo; Jin-Hee Jang;Seong-Ju Kim;Kwang-Yong Gim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.8
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    • pp.21-30
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    • 2023
  • The study proposes a model that utilizes Python-based deep learning text classification techniques to detect the legality of illegal financial advertising posts on the internet. These posts aim to promote unlawful financial activities, including the trading of bank accounts, credit card fraud, cashing out through mobile payments, and the sale of personal credit information. Despite the efforts of financial regulatory authorities, the prevalence of illegal financial activities persists. By applying this proposed model, the intention is to aid in identifying and detecting illicit content in internet-based illegal financial advertisining, thus contributing to the ongoing efforts to combat such activities. The study utilizes convolutional neural networks(CNN) and recurrent neural networks(RNN, LSTM, GRU), which are commonly used text classification techniques. The raw data for the model is based on manually confirmed regulatory judgments. By adjusting the hyperparameters of the Korean natural language processing and deep learning models, the study has achieved an optimized model with the best performance. This research holds significant meaning as it presents a deep learning model for discerning internet illegal financial advertising, which has not been previously explored. Additionally, with an accuracy range of 91.3% to 93.4% in a deep learning model, there is a hopeful anticipation for the practical application of this model in the task of detecting illicit financial advertisements, ultimately contributing to the eradication of such unlawful financial advertisements.

Secret of Old Wine : Focused on Decanting (올드 와인의 비밀 : 디캔팅을 중심으로)

  • Kim, Dong-Joon;Choo, Kou-Jin
    • Journal of Korea Entertainment Industry Association
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    • v.13 no.3
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    • pp.27-41
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    • 2019
  • The study tested the old wines of Château Latour 1953 and tried to analyze the differences from the old wines. Even if not the great vintage, the quality change of old wine gives a new flavor, so it requires analysis results from empirical concepts, decanting, and testing. Based on the analysis results, the government wanted to re-evaluate the old wine and give consumers joy and implications for the wine. The wine to be studied is Château Latour 1953 and is an old wine from the French province of Pauillac. Wine blending is known to be 75% of cabernet sauvignon, 20% of melot, 4% of cabernet franc and 1% of petit verdot. The alcohol level is 13% and the test date is July 2-7, 2018(decanting period 5.4 days/15:00 p.m. on July 7). The testing site was a wine cafe in Daegu City, and the tester consisted of one FICB Korean grand commander and one KOV Finland commander and selected Japchae of Korean food as a mariage. The ullage of Chateau Latour 1953 was 3.0cm and was set up for one month for testing. Decanting time was applied to the calculation formula 2018(current year)-1953(vintage year)/12=5.4 days, which was investigated in this study. Aroma smelled of cork, old grapes, tobacco, leaves and leather, the bouquet was identified in five stages, and the testing was analyzed in seven stages.

Social Perception of the Invention Education Center as seen in Big Data (빅데이터 분석을 통한 발명 교육 센터에 대한 사회적 인식)

  • Lee, Eun-Sang
    • Journal of the Korea Convergence Society
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    • v.13 no.1
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    • pp.71-80
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    • 2022
  • The purpose of this study is to analyze the social perception of invention education center using big data analysis method. For this purpose, data from January 2014 to September 2021 were collected using the Textom website as a keyword searched for 'invention+education+center' in blogs, cafes, and news channels of NAVER and DAUM website. The collected data was refined using the Textom website, and text mining analysis and semantic network analysis were performed by the Textom website, Ucinet 6, and Netdraw programs. The collected data were subjected to a primary and secondary refinement process and 60 keywords were selected based on the word frequency. The selected key words were converted into matrix data and analyzed by semantic network analysis. As a result of text mining analysis, it was confirmed that 'student', 'operation', 'Korea Invention Promotion Association', and 'Korean Intellectual Property Office' were the meaningful keywords. As a result of semantic network analysis, five clusters could be identified: 'educational operation', 'invention contest', 'education process and progress', 'recruitment and support for business', and 'supervision and selection institution'. Through this study, it was possible to confirm various meaningful social perceptions of the general public in relation to invention education center on the internet. The results of this study will be used as basic data that provides meaningful implications for researchers and policy makers studying for invention education.

Analysis of public library book loan demand according to weather conditions using machine learning (머신러닝을 활용한 기상조건에 따른 공공도서관 도서대출 수요분석)

  • Oh, Min-Ki;Kim, Keun-Wook;Shin, Se-Young;Lee, Jin-Myeong;Jang, Won-Jun
    • Journal of Digital Convergence
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    • v.20 no.3
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    • pp.41-52
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    • 2022
  • Although domestic public libraries achieved quantitative growth based on the 1st and 2nd comprehensive library development plans, there were some qualitative shortcomings, and various studies have been conducted to improve them. Most of the preceding studies have limitations in that they are limited to social and economic factors and statistical analysis. Therefore, in this study, by applying the spatiotemporal concept to quantitatively calculate the decrease in public library loan demand due to rainfall and heatwave, by clustering areas with high demand for book loan due to weather changes and areas where it is not, factors inside and outside public libraries and After the combination, changes in public library loan demand according to weather changes were analyzed. As a result of the analysis, there was a difference in the decrease due to the weather for each public library, and it was found that there were some differences depending on the characteristics and spatial location of the public library. Also, when the temperature was over 35℃, the decrease in book loan demand increased significantly. As internal factors, the number of seats, the number of books, and area were derived. As external factors, the public library access ramp, cafe, reading room, floating population in their teens, and floating population of women in their 30s/40s were analyzed as important variables. The results of this analysis are judged to contribute to the establishment of policies to promote the use of public libraries in consideration of the weather in a specific season, and also suggested limitations of the study.