• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.91-108
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• 2020

Korea's famous soccer players are steadily performing well in international leagues, which led to higher interests of Korean fans in the international leagues. Reflecting the growing social phenomenon of rising interests on international leagues by Korean fans, the study examined the overall consumer perception in the consumption of uniform by domestic soccer fans and compared the changes in perception following the transfers of the players. Among others, the paper examined the consumer perception and purchase factors of soccer fans shown in social media, focusing on periods before and after the recruitment of Heung-Min Son to English Premier League's Tottenham Football Club. To this end, the EPL uniform is the collection keyword the paper utilized and collected consumer postings from domestic website and social media via Python 3.7, and analyzed them using Ucinet 6, NodeXL 1.0.1, and SPSS 25.0 programs. The results of this study can be summarized as follows. First, the uniform of the club that consistently topped the league, has been gaining attention as a popular uniform, and the players' performance, and the players' position have been identified as key factors in the purchase and search of professional football uniforms. In the case of the club, the actual ranking and whether the league won are shown to be important factors in the purchase and search of professional soccer uniforms. The club's emblem and the sponsor logo that will be attached to the uniform are also factors of interest to consumers. In addition, in the decision making process of purchase of a uniform by professional soccer fan, uniform's form, marking, authenticity, and sponsors are found to be more important than price, design, size, and logo. The official online store has emerged as a major purchasing channel, followed by gifts for friends or requests from acquaintances when someone travels to the United Kingdom. Second, a classification of key control categories through the convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm shows differences in the classification of individual groups, but groups that include the EPL's club and player keywords are identified as the key topics in relation to professional football uniforms. Third, between 2002 and 2006, the central theme for professional football uniforms was World Cup and English Premier League, but from 2012 to 2015, the focus has shifted to more interest of domestic and international players in the English Premier League. The subject has changed to the uniform itself from this time on. In this context, the paper can confirm that the major issues regarding the uniforms of professional soccer players have changed since Ji-Sung Park's transfer to Manchester United, and Sung-Yong Ki, Chung-Yong Lee, and Heung-Min Son's good performances in these leagues. The paper also identified that the uniforms of the clubs to which the players have transferred to are of interest. Fourth, both male and female consumers are showing increasing interest in Son's league, the English Premier League, which Tottenham FC belongs to. In particular, the increasing interest in Son has shown a tendency to increase interest in football uniforms for female consumers. This study presents a variety of researches on sports consumption and has value as a consumer study by identifying unique consumption patterns. It is meaningful in that the accuracy of the interpretation has been enhanced by using a cluster analysis via convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm to identify the main topics. Based on the results of this study, the clubs will be able to maximize its profits and maintain good relationships with fans by identifying key drivers of consumer awareness and purchasing for professional soccer fans and establishing an effective marketing strategy.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.69-93
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• 2012

Various influence-related relationships in Social Network Services (SNS) among users, posts, and user-and-post, can be expressed using links. The current research evaluates the influence of specific users or posts by analyzing the link structure of relevant social network graphs to identify influential users. We applied the concept of mutual interactions proposed for ranking semantic web resources, rather than the voting notion of Page Rank or HITS, to blogosphere, one of the early SNS. Through many experiments with network models, where the performance and validity of each alternative approach can be analyzed, we showed the applicability and strengths of our approach. The weight tuning processes for the links of these network models enabled us to control the experiment errors form the link weight differences and compare the implementation easiness of alternatives. An additional example of how to enter the content scores of commercial or spam posts into the graph-based method is suggested on a small network model as well. This research, as a starting point of the study on identifying influential users in SNS, is distinctive from the previous researches in the following points. First, various influence-related properties that are deemed important but are disregarded, such as scraping, commenting, subscribing to RSS feeds, and trusting friends, can be considered simultaneously. Second, the framework reflects the general phenomenon where objects interacting with more influential objects increase their influence. Third, regarding the extent to which a bloggers causes other bloggers to act after him or her as the most important factor of influence, we treated sequential referencing relationships with a viewpoint from that of PageRank or HITS (Hypertext Induced Topic Selection).

• Journal of Korean Home Economics Education Association
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• v.16 no.3
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• pp.131-146
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• 2004

The Purpose of this study is to suggest strategies for environmental education through the Practical Arts(TechnologyㆍHome economics) Subject in a viewpoint of the clothing & textiles resources to resolve problems in the clothing life area. For this, this study was carried out through review of literature which is related with the consumption, the environmental problems, the environmental policies, and regulations of the government and new environmental technologies, of clothing & textiles industries and environmental education. The major findings of the study were as follows; 1) The environmental education system model in a viewpoint of the Clothing & Textiles resources was developed. This model system is consisted with interactions on school, government, industry, home and non-government organizations. Thus, the fact that Practical Arts(TechnologyㆍHome economics) Subject were the most effective subject to teaching the environmental education viewpoint of the Clothing & Textiles resources was confirmed. 2) The standards were analysed out to analyse the contents in the clothing area of the Practical Arts(TechnologyㆍHome economics) Subject. It were consist of 4 factors and 12 elements under the factors: Awareness of clothing & textile resources(clothing consumption, production of clothing & textile and environmental problems). Planning and buying of clothing(planning, buying), Management of clothing(understand of textile. human body & environment, laundering and Environmental pollution, arrangement & conservation) Recycling & exhaust of clothing(contribution, redesign, recycling, exhaust) 3) Analysing the current Practical Arts (TechnologyㆍHome economics) subject from the Environmental education in the clothing section, the environmental education related with clothing were taught the most in the middle school course, and environmental contents were concentrated in the recycling factors. but not so much on other factors. 4) After analysing the Practical Arts (TechnologyㆍHome economics) subject, the strategies were suggested for reinforcing the environmental education in the clothing of the Practical Arts(TechnologyㆍHome economics) subject.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.55-72
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• 2021

This study aims to research the influences of the discrimination of internet media and one-person media environment, especially, the one-person media creators leading the mobile media that could be accessed and viewed anywhere, on the user attitude and continuous subscription intention. Especially, this study aimed to understand the current situation of one-person media market represented as YouTube, to explore the relationship and ecology between each subject and elements composing the media market, and also to understand the mediating effects of the characteristics of YouTube creators on the relation between contents involvement and user attitude, and the relation between user attitude and subscription intention, and the mediating effects of contents involvement on the relation between characteristics of creators and user attitude. As research methods, first, for the theoretical establishment, this study collected, conducted, and organized the published domestic/foreign theses/journal papers. For the objective validity and verification of the established research model, a survey was conducted targeting adult men and women currently watching YouTube, and then the empirical analysis was performed through the final effective samples. And the results of this study are as follows. First, the playfulness and reliability on the relation between characteristics of creators and contents involvement were not significant while the professionalism was significant. Second, the professionalism on the relation between characteristics of creators and user attitude was not significant while the playfulness and reliability were significant. Third, the relation between contents involvement and user attitude was significant. Fourth, the relation between user attitude and subscription intention was also significant. Also, in the results of verifying the mediating effects of contents involvement, the contents involvement completely mediated the relation between characteristics(playfulness, reliability, and professionalism) of creators and user attitude. And in the conclusion, this study presented the implications and suggestions for further researches in the future.