• Journal of Fashion Business
• /
• v.27 no.3
• /
• pp.132-149
• /
• 2023

This study aims to analyze Instagram hashtags based on big data to investigate changes in consumer trends and perceptions of vegan fashion, and to derive strategies for revitalizing vegan fashion brands based on derived results. Among social media, Instagram was selected as a collection channel, and Instagram hashtags for 'Vegan Fashion' were collected from July 1, 2021 to December 31, 2021. After conducting semantic network analysis with the Ucinet 6 program based on the collected data, the CONCOR analysis on vegan fashion showed the following four clusters: 'Veganism practiced with fashion', 'Bag type of vegan fashion brand', 'Sharing vegan fashion', and 'Diversification of eco-friendly products'. Analysis results showed that the Instagram hashtag for vegan fashion confirmed the MZ generation's increased interest in vegan fashion and their thoughts to recommend and share frequently used items or brand products to people around them. CONCOR analysis of vegan fashion brands showed the following four groups: 'Differentiating the material of vegan bags', 'Eco-friendly products of vegan fashion brands', 'Interest in vegan shoes', and 'Donation campaign of vegan fashion brands'. CONCOR analysis on Meaningout showed the following four clusters: 'MZ Generation's Meaningout Start-up', 'Recommendation Platform for Skin Products', 'Value Consumption Trend for Eco-friendly Clothing', and 'Interest in Eco-friendly Packaging'. The results of this study on vegan fashion, a practical eco-friendly movement that can require changes in social responsibility and perception as issues that directly affect animals, the environment, and humans, are expected to provide basic data to help domestic vegan fashion brands develop marketing strategies.

• Journal of Korean Library and Information Science Society
• /
• v.54 no.4
• /
• pp.255-279
• /
• 2023

The purpose of this study is to derive implications through a comparison of the current status of catalog enriched content services provision in U.S. public libraries and domestic public libraries. In addition, we are seeking ways to improve the catalog enriched content services for domestic public libraries in the future. From early September to mid-October 2023, specific books were searched on public library websites in the U.S. and Korea, and the functions of the enriched content services shown in the search results were compared. The results are as follows: First, domestic public library enriched content services require a separate company to develop and provide an enriched content services solution. Second, the enriched content services platform must discover domestic information sources that can be utilized in the areas of book-centered, book recommendation, and community engagement. Third, it is necessary to develop enriched content using public data such as the Library Information Naru. Fourth, each integrated library must that data generated from local community engagement services can be utilized as an enriced content service.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.6
• /
• pp.309-314
• /
• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• Journal of Korean Society of Steel Construction
• /
• v.29 no.1
• /
• pp.49-60
• /
• 2017

As well as the strength check, fatigue life check is also mainly required for designing mooring lines of the floating structures. In general, forces which induce dynamic structural response significantly affect to fatigue design of the mooring lines. So, waves are mainly considered as the governing loading for fatigue design of the mooring lines. In this study, characteristics of the fatigue damage of the mooring lines for submerged floating tunnels (SFT) under irregular waves are investigated. For this study time domain hydrodynamic analysis is used to obtain motion of the tunnel and tension and stresses of the mooring lines under the specific environmental conditions. Also, the Rainflow-counting method, the Palmgren-Miner's rule, and S-N curves for floating offshore structures presented by DNV recommendation is applied to calculate the fatigue damage due to the fluctuating stresses. Referring to the design plactice of the tendon pipes for TLP (tension-leg platform), which is very similar structural system to SFT, it is assumed that a 100 year return period wave attacks the SFT systems during 48 hours and the fatigue damages due to the environmental loading are calculated. Following the analysis sequence, the effects of the tunnel draft, spacing and initial inclination angle of the mooring lines on the fatigue damage under the specific environmental loadings are investigated.

• The Journal of KAIRB
• /
• v.3 no.1
• /
• pp.11-18
• /
• 2021

Purpose: The purpose of this study is to investigate a satisfaction survey of untact education and platforms that can be used for untact education to provide recommendations on future development of Education of Persons Conducting Clinical Trials. Methods: Online survey was distributed among students who have taken Untact Education of Persons Conducting Clinical Trials. The result was separated according to topic and descriptive statistics was used for analysis. The satisfaction survey used 10-point scale. Results: Of the 1,720 students who received the survey, 1,347 (78.3%) responded to the lecture satisfaction survey. The satisfaction level for broadcasting program (Kakao TV), an untact educational platform for the education of clinical trial workers at Kyung Hee University Medical Center, was relatively high with 8.09±1.99 points. Average score respondents recommending Kyung Hee University Untact Education of Persons Conducting Clinical Trials was 8.03±1.83 and customer recommendation score (Net Promotor Score) was 27.1%. Satisfaction level of the preferred training time was divided into weekday-morning (8-11 AM) (8.16±1.75), weekday-afternoon (12-4 PM) (7.73±2.07), weekday-evening (5-9 PM) (7.78±2.22), and weekend-morning (9-11 AM) real-time untact education (8.48±1.76) and analyzed. There was a noticeable difference between weekend-morning and weekday-afternoon (p<0.0001) and weekend-morning and weekday-evening (p=0.0001) real-time untact education. When asked about conducting education after COVID-19 pandemic ends, 79.2% (1,012 of 1,279) of the respondents answered that they prefer real-time untact education while 20.8 % (266 of 1,279) preferred face-to-face education. Conclusion: Online education, without time and space constraint, is expected to be the mainstream market in Korea for Education of Persons Conducting Clinical. Kyung Hee University Untact Education of Persons Conducting Clinical has achieved above average satisfaction using Kakao TV. Kyung Hee University Real-time Untact Education of Persons Conducting Clinical Net Promotor Score is 27.1%, which is above industry average, communication with trainees should be considered to improve Net Promotor Score.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.3
• /
• pp.527-535
• /
• 2021

Traditional business intelligence (BI) systems have been used widely as tools for better decision-making on time. On the other hand, building a data warehouse (DW) for the efficient analysis of rapidly growing data is time-consuming and complex. In particular, the ETL (Extract, Transform, and Load) process required to build a data warehouse has become much more complex as the BI platform moves to a cloud environment. Various BI solutions based on the NoSQL database, such as MongoDB, have been proposed to overcome these ETL issues. Decision-makers want easy access to data without the help of IT departments or BI experts. Recently, self-service BI (SSBI) has emerged as a way to solve these BI issues. This paper proposes a self-service BI system with farming data using the MongoDB cloud as DW to support the selection of new crops by return-farmers. The proposed system includes functions to provide insights to decision-makers, including data visualization using MongoDB charts, reporting for advanced data search, and monitoring for real-time data analysis. Decision makers can access data directly in various ways and can analyze data in a self-service method using the functions of the proposed system.

• Journal of Intelligence and Information Systems
• /
• v.29 no.4
• /
• pp.1-13
• /
• 2023

The widespread adoption of smartphones and advancements in internet technology have notably shifted content consumption habits toward video. This research aims to dissect the nature of videos posted on YouTube, the global video-sharing platform, to understand the characteristics of both produced and preferred content. For this study, dance was chosen as a specific subject from a variety of video categories. Data on YouTube videos associated with the term "dance" was compiled over three years, from 2019 to 2021. The investigation revealed a clear distinction between the types of dance videos frequently uploaded to YouTube and those that receive a high number of views. The empirical analysis of this study indicates a viewer preference for vlogs that provide insights into the daily lives of dance students, as well as for purpose-driven videos, such as those highlighting dance exam preparations or school dance events. Notably, the vlogs that attract the most attention are typically created by dance students at the college or secondary school level, rather than by professionals. Although the study was focused on dance, its methodologies can be applied to different subjects. These insights are expected to contribute to the development of a recommendation system that aids content creators in effectively targeting their productions.

• Korean Journal of Radiology
• /
• v.21 no.4
• /
• pp.422-430
• /
• 2020

The Korean Society of Urogenital Radiology (KSUR) aimed to present a consensus statement for patient preparation, standard technique, and pain management in relation to transrectal ultrasound-guided prostate biopsy (TRUS-Bx) to reduce the variability in TRUS-Bx methodologies and suggest a nationwide guideline. The KSUR guideline development subcommittee constructed questionnaires assessing prebiopsy anticoagulation, the cleansing enema, antimicrobial prophylaxis, local anesthesia methods such as periprostatic neurovascular bundle block (PNB) or intrarectal lidocaine gel application (IRLA), opioid usage, and the number of biopsy cores and length and diameter of the biopsy needle. The survey was conducted using an Internet-based platform, and responses were solicited from the 90 members registered on the KSUR mailing list as of 2018. A comprehensive search of relevant literature from Medline database was conducted. The strength of each recommendation was graded on the basis of the level of evidence. Among the 90 registered members, 29 doctors (32.2%) responded to this online survey. Most KSUR members stopped anticoagulants (100%) and antiplatelets (76%) one week before the procedure. All respondents performed a cleansing enema before TRUS-Bx. Approximately 86% of respondents administered prophylactic antibiotics before TRUS-Bx. The most frequently used antibiotics were third-generation cephalosporins. PNB was the most widely used pain control method, followed by a combination of PNB plus IRLA. Opioids were rarely used (6.8%), and they were used only as an adjunctive pain management approach during TRUS-Bx. The KSUR members mainly chose the 12-core biopsy method (89.7%) and 18G 16-mm or 22-mm (96.5%) needles. The KSUR recommends the 12-core biopsy scheme with PNB with or without IRLA as the standard protocol for TRUS-Bx. Anticoagulants and antiplatelet agents should be discontinued at least 5 days prior to the procedure, and antibiotic prophylaxis is highly recommended to prevent infectious complications. Glycerin cleansing enemas and administration of opioid analogues before the procedure could be helpful in some situations. The choice of biopsy needle is dependent on the practitioners' situation and preferences.

• Journal of Intelligence and Information Systems
• /
• v.19 no.4
• /
• pp.39-53
• /
• 2013

The emergence of the internet technology and SNS has increased the information flow and has changed the way people to communicate from one-way to two-way communication. Users not only consume and share the information, they also can create and share it among their friends across the social network service. It also changes the Social Media behavior to become one of the most important communication tools which also includes Social TV. Social TV is a form which people can watch a TV program and at the same share any information or its content with friends through Social media. Social News is getting popular and also known as a Participatory Social Media. It creates influences on user interest through Internet to represent society issues and creates news credibility based on user's reputation. However, the conventional platforms in news services only focus on the news recommendation domain. Recent development in SNS has changed this landscape to allow user to share and disseminate the news. Conventional platform does not provide any special way for news to be share. Currently, Social News Service only allows user to access the entire news. Nonetheless, they cannot access partial of the contents which related to users interest. For example user only have interested to a partial of the news and share the content, it is still hard for them to do so. In worst cases users might understand the news in different context. To solve this, Social News Service must provide a method to provide additional information. For example, Yovisto known as an academic video searching service provided time dependent metadata from the video. User can search and watch partial of video content according to time dependent metadata. They also can share content with a friend in social media. Yovisto applies a method to divide or synchronize a video based whenever the slides presentation is changed to another page. However, we are not able to employs this method on news video since the news video is not incorporating with any power point slides presentation. Segmentation method is required to separate the news video and to creating time dependent metadata. In this work, In this paper, a time dependent metadata-based framework is proposed to segment news contents and to provide time dependent metadata so that user can use context information to communicate with their friends. The transcript of the news is divided by using the proposed story segmentation method. We provide a tag to represent the entire content of the news. And provide the sub tag to indicate the segmented news which includes the starting time of the news. The time dependent metadata helps user to track the news information. It also allows them to leave a comment on each segment of the news. User also may share the news based on time metadata as segmented news or as a whole. Therefore, it helps the user to understand the shared news. To demonstrate the performance, we evaluate the story segmentation accuracy and also the tag generation. For this purpose, we measured accuracy of the story segmentation through semantic similarity and compared to the benchmark algorithm. Experimental results show that the proposed method outperforms benchmark algorithms in terms of the accuracy of story segmentation. It is important to note that sub tag accuracy is the most important as a part of the proposed framework to share the specific news context with others. To extract a more accurate sub tags, we have created stop word list that is not related to the content of the news such as name of the anchor or reporter. And we applied to framework. We have analyzed the accuracy of tags and sub tags which represent the context of news. From the analysis, it seems that proposed framework is helpful to users for sharing their opinions with context information in Social media and Social news.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.179-196
• /
• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.