• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2005.11a
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• pp.73-77
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• 2005

To design senior housing that support residents' health is one of the comtemporary issues in Korea. As elderly people became more healthful and reach, people became interested in the health and health promotion. This trend encouraged this research study. The objectives of this study are: to analyze the middle aged people's opinions and behaviors related to health issues, and to suggest design considerations for senior housing. The survey used questionnaire from 476 residents living in Seoul and Gyeong-Gi area. The analysis used descriptive statistics, one-way anova and t-test. Primary findings are as follows: (1) Most of the respondents considered that their health state is 'good' and mental health is more important than physical health. (2) Many people exercise regularly for the promotion of health at a gym. (3) Results show that social relationship effect on health, and dietary life and walking medical examination account highly. (4) As the respondents are higher income and education level, the health-related behavior is more actively. Moreover the respondents who are women feel a great interest about health issues. These results suggest directions for planning of the senior housing. (1) Planning the space for the health-promoting behavior in the house or support a private gym-not a local facilities-. (2) Service for the information related health issues - medical examination, news of the health issues (3) Support the maintenance a good - social relationship (4) Consideration the space with health-related behavior like walking and dietary-life. The senior housing can reflect the health-related opinions and support health-related behavior of the elderly people.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.195-200
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• 2019

The purpose of this paper is to explore security guard's status and roles in society through media reports. Research method is to anlyze security Guard's 'Keyword Trend' and 'Keyword Frequency Analysis' by 'Big Kind' which enables 'News Big Data' analysis. The result came out by the analysis in sectional private security guard's history of settling down, growing up (quantity), and growing up (quality) by separating generations is that there are lots of attention and exposure from media about crime, security guard job, minimum wage, and 'Gabjil', but the images of security guard are recognized as victim of crime and 'Gabjil', and working in poor environment with minimum waged and ambiguous job, instead of people preventing crimes. In the future, stabilizing security guard's social status and work responsibility, and developing job professionalism are necessary to improve the images of security guard.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.269-275
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• 2022

As artificial intelligence services targeting humans increase, social demands are increasing that artificial intelligence should also be made on an ethical basis. Following this trend, the government and businesses are preparing policies and norms related to artificial intelligence ethics. In order to establish reasonable policies and norms, the first step is to understand the public's perceptions. In this paper, social data and news comments were collected and analyzed to understand the public's perception related to artificial intelligence and ethics. Interest analysis, emotional analysis, and discourse analysis were performed and visualized on the collected datasets. As a result of the analysis, interest in "artificial intelligence ethics" and "artificial intelligence" favorability showed an inversely proportional correlation. As a result of discourse analysis, the biggest issue was "personal information leakage," and it also showed a discourse on contamination and deflection of learning data and whether computer-made artificial intelligence should be given a legal personality. This study can be used as data to grasp the public's perception when preparing artificial intelligence ethical norms and policies.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.712-720
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• 2022

The use of social media to disseminate news and interact with project stakeholders is increasing over time in the construction industry. Such social media data can be analyzed to get useful insights of the industry such as demands of new housing construction and satisfaction of construction workers. However, there has been a limited attempts to analyze social media data related to the construction industry. The objective of this study is to collect and analyze construction related tweets to understand the overall sentiments of individuals and organizations about the construction industry. The study collected 87,244 tweets from April 6, 2020, to April 13, 2020, which had hashtags relevant to the construction industry. The tweets were then analyzed to evaluate its sentiments polarity (positive or negative) and sentiment intensity or scores (-1 to +1). Descriptive statistics were produced for the tweets and the sentiment scores were visualized in a scatterplot to show the trend of the sentiment scores over time. The results shows that the overall sentiment score of all the tweets was slightly positive (0.0365). Negative tweets were retweeted and marked as favorite by more users on average than the positive ones. More specifically, the tweets with negative sentiments were retweeted by 2,802 users on average compared to the tweets with positive sentiments (247 average retweet count). This study can potentially be expanded in the future to produce a real time indicator of the construction market industry such as the increased availability of construction jobs, improved wage rates, and recession.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.65-76
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• 2023

In the field of technology entrepreneurship and startups, the development of Artificial Intelligence(AI) has emerged as a key topic for business model innovation. As a result, venture firms are making various efforts centered on AI to secure competitiveness(Kim & Geum, 2023). The purpose of this study is to analyze the relationship between the development of GenAI technology and the startup ecosystem by analyzing domestic news articles to identify trends in the technology startup field. Using BIG Kinds, this study examined the changes in GenAI-related news articles, major issues, and trends in Korean news articles from 1990 to August 10, 2023, focusing on the emergence of ChatGPT before and after, and visualized the relevance through network analysis and keyword visualization. The results of the study showed that the mention of GenAI gradually increased in the articles from 2017 to 2023. In particular, OpenAI's ChatGPT service based on GPT-3.5 was highlighted as a major issue, indicating the popularization of language model-based GenAI technologies such as OpenAI's DALL-E, Google's MusicLM, and VoyagerX's Vrew. This proves the usefulness of GenAI in various fields, and since the launch of ChatGPT, Korean companies have been actively developing Korean language models. Startups such as Ritten Technologies are also utilizing GenAI to expand their scope in the technology startup field. This study confirms the connection between GenAI technology and startup entrepreneurship activities, which suggests that it can support the construction of innovative business strategies, and is expected to continue to shape the development of GenAI technology and the growth of the startup ecosystem. Further research is needed to explore international trends, the utilization of various analysis methods, and the possibility of applying GenAI in the real world. These efforts are expected to contribute to the development of GenAI technology and the growth of the startup ecosystem.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• Journal of Families and Better Life
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• v.24 no.1 s.79
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• pp.129-140
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• 2006

The purpose of this study was to understand the labor division between men's housework and market work and to research the change of men's contribution to housework. And it was also examined what kinds of valuables work on a change in men's market work and housework. The information about men's change in the labor division was collected from the biggest 5 news papers in Korea for last five years for this study. And either men's new participation trend to household work did. Words searched for this study were men, labor, family, home, housewife, work, household work, father etc. Korean men have experienced a overloaded breadwinner role and have worked most in the world since 1960s. But Korean men's working time was continuously decreased a little every year. As Korean Companies had fired many worker during IMP economic crisis period, Korean men had to work more than before because of decreased fellows and they should have concentrated on their work at the sacrifice of private life and family-sharing time. On the other hand, some men were started to participate to do housework as a results of long-unemployment and early retirement after this periods. 5 day working system be in forced gradually since 2003 especially make men come back home and interest on housework. So Korean men's housework participation is gradually increasing by the practical application of sex-equitable politics such as 5 day working system and men's suspension regime for baby care. father's increased participation to children education and care, men's new family-oriented life style, dual-sexuality education system, and socially changed perception to husband housemaker. These interrelated trends demands us to shape a new labor division pattern in the family that make change the breadwinner/homemaker conception by the gender role. Now, all of family, men, women, and children have to join housework. It would help women, men, and all families make more human and equitable relationship.

• The Research Journal of the Costume Culture
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• v.19 no.2
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• pp.283-295
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• 2011

This study deals with the interchange with art that is contained in the works of Yves Saint Laurent, and it is disclosed through his works that modern fashion is part of expressive art while pursuing creative function as a work of art. The study has been performed on the basis of the references, the pictures of his works and interviews posted in domestic and overseas fashion magazines such as Vogue, Fashion News, Mode & Mode, Gap, Collections, etc. Regarding the scope of this study, it specifically deals with works he created from 1958 until 2002, when he announced his last collection. The results of the study show that with respect to Post-Impressionism, his works were greatly affected by van Gogh(who had used colors as active media in depicting his internal mental state) which gave birth to gorgeous and handicraft-like 'Couture-style clothes'. With respects to Fauvism, the works of Matisse also had an impact on Yves Saint Laurent, who added a sense of fauvism in his works through the use of colors, motif, or full reproduction of images from paintings. We see the influence of cubism upon Laurent when we examine his works of 'clothes with artistic value,' which utilized applique, beaded decoration, patchwork, embroidered patterns, relief-like ornaments, etc. using motif or objet much as we see in the works of Picasso and Braque, artists who expressed a new dimension of the formative arts. Laurent's use of neoplasticism, or plainness of painting, demonstrates a new formative art on the three-dimensional human body by using the works of Mondrian, which consist of black lines and primary colors, although generally Laurent's 'neoplastic'works differed from the works of Mondrian by more actively utilizing the lines and colors when designing dress and its ornament. In addition, the paintings and poems of surrealism artists and poets were directly used in the clothes or their images were sometimes borrowed. In order to express respect toward the spirit of surrealism and its artists, the human body motifs such as lips and eyes(which were frequently used by the surrealism artists) were applied to embroidery, printing and beaded decoration. Finally, being inspired by such Pop artists as Andy Warhol, Roy Lichtenstein and Tom Wesselman, Laurent further emphasized the aesthetic value of the popular consumer image in his own work, resulting in the wide recognition of the designs of Yves Saint Laurent as representing the new wave of the Pop Art school.

• Science of Emotion and Sensibility
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• v.19 no.3
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• pp.59-70
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• 2016

Qualitative consumption is a trend in the children clothing market and watching TV of childcare-entertainment reality programs are becoming popular. This study examines the watching degree of childcare-entertainment reality TV programs of parent buyer (30s) and potential buyer (20s) and we investigate their shopping orientation of children wear. We did the survey research of 200 consumers with SPSS statistical analysis including the review of internet news, paper, and books on children wear shopping orientation. The results are following: first, the longer the watching time of childcare-entertainment reality TV programs, the higher shopping orientation, such as following the fashion of child stars, and the higher the watching preferences on childcare-entertainment reality programs, the greater shopping orientation in following childcare-entertainment reality programs star when they are purchasing children's clothing. Second, potential consumers as well as parent consumers were affected by watching the childcare-entertainment reality programs. Watching childcare-entertainment reality TV programs could give the impact when they were shopping children's clothing because they wanted to follow the fashion of childcare-entertainment reality programs TV star. Accordingly, the exposure of the childcare-entertainment reality programs for children clothing is found to be positive to the both current and future consumers.