• Journal of Digital Convergence
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• v.17 no.7
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• pp.35-41
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• 2019

This study aims to analyze the cosmedical cosmetics market and the nature of customer through the social big data analysis. More than 80,000 posts were analyzed using R program. After data cleansing, keyword frequency analysis and association analysis were performed to understand customer needs and competitor positioning, formulated several implications for marketing strategy sophistication and implementation. Analysis results show that "prevention" is a new and essential attribute for appealing target customers. The expansion of the product line for the gift market is also suggested. It has been shown that there is a high correlation with products that can be complementary to each other. In addition to the traditional marketing technique, the social big data analysis based on evidence was useful in deriving the characteristics of the customers and the market that had not been identified before. Word2vec algorithm will be beneficial to find additional.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.398-398
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• 2022

최근 수돗물 공급과정에 있어 적수, 유충 발생 등 지역 단위의 수질문제로 국민의 직간접적인 피해가 발생된 바 있다. 수질문제 발생 시, 소셜네트워크서비스(SNS)에 게시되는 피해 관련 의견은 시공간적으로 빠르게 확산되며, 궁극적으로는 물공급과정 전체의 부정적 인식증가와 신뢰도 저하를 초래한다. 따라서, 물공급시스템에서의 수질사고 발생을 빠르게 인지하는 다양한 방법론의 적용을 통한 피해 최소화를 위한 노력이 반드시 필요하다. 일반적으로 수질사고는 다양한 항목의 실시간 계측기에서 획득되는 시계열자료의 변화양상을 통해 판단할 수 있으나, 이와 같은 방법론의 효율적 적용을 위해서는 선진계측인프라의 도입이 선행되어야 한다. 본 연구에서는 국내의 발달된 정보통신기술환경을 활용하여, 물공급네트워크 내 수질사고인지를 위한 SNS 별 웹크롤링 방법론을 제안하고, 적용결과를 분석하였다. 방법론의 구현에 앞서, 각종 SNS 별(트위터, 인스타그램, 블로그, 네이버 카페 등) 프로그래밍을 통한 웹크롤링 가능여부, 정보획득 기간 등을 확인하였으며, 과거 유사 수질사고 발생 시 영향력과 관련 게시글이 크게 나타난 네이버 카페와 트위터를 중심으로 웹 크롤링 절차를 제시하였다. 네이버 카페의 경우 대상급수구역 내의 시민들이 다수 참여하는 카페를 목록화하고, 지자체명과 핵심 키워드(수돗물, 유충, 적수) 조합을 활용한 웹크롤링을 수행하여, 관련 게시물 건수와 의미를 실시간으로 분석하는 절차를 마련하였다. 개발된 SNS 별 웹크롤링 방법론에 따라 과거 수질사고가 발생된 바 있는 2개 이상의 지자체에 대한 분석을 실시하였으며, SNS 별 결과에 있어 차이점을 확인하여 제시하였다. 향후 제안된 방법을 적용하여 시공간적 수질사고 정보의 전파 및 확산양상을 추가적으로 분석할수 있을 것으로 기대된다.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.6
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• pp.64-79
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• 2021

In Korea, mountains constitute 60 percent of the total land area. For a long time, mountains have been deeply involved in people's daily lives, acting as a significant layer of culture. For those reasons, it would be meaningful to shed light on the values of the mountain culture of Korea and seek various ways to utilize them. Therefore, this study aims to explore Korea's mountain enjoyment culture, considering the mountain leisure in the Joseon Dynasty period, when the heritage of mountain enjoying culture was prevalent, and that of the present era. For the analysis, hiking records of the Joseon Dynasty and present-day hiking blog posts related to three famous mountains in Korea were examined. Findings show that people stayed in the mountains for a long time in the Joseon Dynasty, concentrating on the landscape deeply, and various academic and artistic cultures flourished there. In contrast, contemporary people regard the mountain merely as a space to access the peak and climb down quickly within a day. Therefore, the landscape of the mountain cannot be used as a cultural asset beyond natural scenery. However, there are several positive aspects to today's climbing culture. For example, it is easy to obtain information on climbing and feasible ways to conduct various sizes and concepts of hiking due to the development of technology and transportation. In order to develop Korea's unique mountain enjoyment culture in the future, we should propose a 'leisurely hike' that allows people to enjoy the mountain scenery fully and sublimating it into culture, rather than being hiking that is limited to climbing. In addition, it is essential to create suitable spaces, arranging them appropriately to utilize the history and humanities context of the mountain, and connect local facilities and the workforce, thereby causing the development of various mountain enjoyment cultures.

• The Korean Journal of Archival Studies
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• no.46
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• pp.95-152
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• 2015

"Archives of Everyday Life" refers to an organization or facility which collects, appraises, selects and preserves the document from the memory of individuals, groups, or a society through categorizing and classifying lives and cultures of ordinary people. The document includes materials such as diaries, autobiography, letters, and notes. It also covers any digital files or hypertext like posts from blogs and online communities, or photos uploaded on Social Network Services. Many research fields including the Records Management Studies has continuously claimed the necessity of collection and preservation of ordinary people's records on daily life produced every moment. Especially diary is a written record reflecting the facts experienced by an individual and his self-examination. Its originality, individuality and uniqueness are considered truly valuable as a document regardless of the era. Lately many diaries have been discovered and presented to the historical research communities, and diverse researchers in human and social studies have embarked more in-depth research on diaries, their authors, and social background of the time. Furthermore, researchers from linguistics, educational studies, and psychology analyze linguistic behaviors, status of cultural assimilation, and emotional or psychological changes of an author. In this study, we are conducting a metastudy from various research on diaries in order to reaffirm the value of "The 12th May Diaries Collection" as everyday life archives. "The 12th May Diaries Collection" consists of diaries produced and donated directly by citizens on the 12th May every year. It was only 2013 when Digital Archiving Institute in Univ. of Myungji organized the first "Annual call for the 12th May". Now more than 2,000 items were collected including hand writing diaries, digital documents, photos, audio and video files, etc. The age of participants also varies from children to senior citizens. In this study, quantitative analysis will be made on the diaries collected as well as more profound discoveries on the detailed contents of each item. It is not difficult to see stories about family and friends, school life, concerns over career path, daily life and feelings of citizens ranging all different generations, regions, and professions. Based on keyword and descriptors of each item, more comprehensive examination will be further made. Additionally this study will also provide suggestions to examine future research opportunities of these diaries for different fields such as linguistics, educational studies, historical studies or humanities considering diverse formats and contents of diaries. Finally this study will also discuss necessary tasks and challenges for "the 12th May Diaries Collection" to be continuously collected and preserved as Everyday Life Archives.

• Journal of KIISE:Software and Applications
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• v.37 no.6
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• pp.455-463
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• 2010

In this paper, we present an approach to sentence boundary detection for web documents that builds on statistical-based methods and uses rule-based correction. The proposed system uses the classification model learned offline using a training set of human-labeled web documents. The web documents have many word-spacing errors and frequently no punctuation mark that indicates the end of sentence boundary. As sentence boundary candidates, the proposed method considers every Ending Eomis as well as punctuation marks. We optimize engine performance by selecting the best feature, the best training data, and the best classification algorithm. For evaluation, we made two test sets; Set1 consisting of articles and blog documents and Set2 of web community documents. We use F-measure to compare results on a large variety of tasks, Detecting only periods as sentence boundary, our basis engine showed 96.5% in Set1 and 56.7% in Set2. We improved our basis engine by adapting features and the boundary search algorithm. For the final evaluation, we compared our adaptation engine with our basis engine in Set2. As a result, the adaptation engine obtained improvements over the basis engine by 39.6%. We proved the effectiveness of the proposed method in sentence boundary detection.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.571-579
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• 2020

The purpose of the study was to explore modern people's emotion regarding sex commercialization related to the abolition of grid girl. To collect data, based on 'reply journalism', this study collected 15 blogs, 10 online cafe contents, 1 youtube video clip, and 364 replies associated with the three online contents. To analyze the data, interpretive text analysis was utilized and the following results were obtained. As results, the analysis on the replies shows that the most strong emotion of the modern people regarding the abolition of grid girl is anti-feminism that includes hatred toward feminists and even females, criticism on feminism, and notion of 'women's enemy is women themselves'. In addition, sympathy toward racing models who lost their jobs, requirement of same abolition to the people with similar occupations, spatial separation between men and women, and consent on the abolition of racing models were found. Unlike the feminists' emotion regarding sex commercialization and racing models, modern people's emotion was different from them. Rather, ordinary people have doubted and even criticized on the rationales of feminism. Unlike feminists' notion about sex commercialization of racing models, these results imply that social image of racing models has changed and wish their position is respected as an ordinary occupation, without issues of sex commercialization.

• Child Health Nursing Research
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• v.20 no.1
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• pp.49-57
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• 2014

Purpose: The purpose of this qualitative study was to explore how adolescent survivors of childhood cancer grieve the death of cancer peers. Methods: Data were obtained from Korean adolescents with cancer between the ages of 13 and 18 (N=12) through semi-structured interviews (face-to-face, telephone, and Internet chatting), observations of the social dynamics of participants in self-help groups, and retrieval of personal Web journals. Based on the grounded theory methodology, data collection and analysis were conducted simultaneously, and constant comparative methods were used. Clarke's situational analysis was adopted, and this paper focused on presenting "how to" and "what we can learn" from this analytic strategy. Results: Mapping examples were visualized using of three modes of maps. Adolescent cancer survivors coped with reminders of the "darkness" that ultimately featured their overall grief. Additionally, adolescents' encounters and avoidance of grief were triggered by introspection and interactions with family and friends. Conclusion: Situational analysis provided an efficient way to analyze the experiences of adolescent survivors of childhood cancer by systematizing possible information within the relational social contexts of the research phenomenon.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.29-43
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• 2021

Coinciding with the advent of COVID-19, online education is on the rise both domestically and globally, and has become an absolutely necessary and irreplaceable form of education. It is a very curious question what the perception of people about the suddenly growing form of education is, and how it has changed. This study investigated changes in consumers' perception of online education using big data. To this end, we divided the time into four stages: before COVID-19 (November to December 2019), after the triggering of COVID-19 (January to February 2020), right after the online classes started (March to April 2020), after experiencing some online education (May to June 2020). Then we conducted text mining, namely, keyword frequency analysis, network analysis, word cloud analysis, and sentiment analysis were performed. The implications derived as a result of the analysis can help education policy makers and educators working in the field to improve online education quality and establish its future directions.

• 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.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.5
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• pp.10-21
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• 2018

This study used text mining methodology to focus on the perceptions of the landscape embedded in text that users spontaneously uploaded to the "Taean Travel"blogpost. The study area is the Taean Coast National Park. Most of the places that are searched by 'Taean Travel' on the blog were located in the Taean Coast National Park. We conducted a network analysis on the top three places and extracted keywords related to the landscape. Finally, using a centrality and cohesion analysis, we derived landscape perceptions and the major characteristics of those landscapes. As a result of the study, it was possible to identify the main tourist places in Taean, the individual landscape experience, and the landscape perception in specific places. There were three different types of landscape characteristics: atmosphere-related keywords, which appeared in Kkotji Beach, symbolic image-related keywords appeared in Sinduri Coastal Sand Dune, and landscape objects-related appeared in Manlipo Beach. It can be inferred that the characteristics of these three places are perceived differently. Kkotji Beach is recognized as a place to appreciate a view the sunset and is a base for the Taean Coast National Park's trekking course. Sinduri Coastal Sand Dune is recognized as a place with unusual scenery, and is an ecologically valuable space. Finally, Manlipo Beach is adjacent to the Chunlipo Arboretum, which is often visited by tourists, and the beach itself is recognized as a place with an impressive appearance. Social media data is very useful because it can enable analysis of various types of contents that are not from an expert's point of view. In this study, we used social media data to analyze various aspects of how people perceive and enjoy landscapes by integrating various content, such as landscape objects, images, and activities. However, because social media data may be amplified or distorted by users' memories and perceptions, field surveys are needed to verify the results of this study.