• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.39-45
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• 2018

Twitter users use 'Following', 'Retweet' and so on to find tweets that they are interested in. However, it is difficult for users to find tweets that are of interest to them on Twitter, which has more than 300 million users. In this paper, we developed a customized tweet recommendation system to resolve it. First, we gather current trends to collect tweets that are worth recommending to users and popular tweets that talk about trends. Later, to analyze users and recommend customized tweets, the users' tweets and the collected tweets are categorized. Finally, using Web service, we recommend tweets that match with user categorization and users whose interests match. Consequentially, we recommended 67.2% of proper tweet.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.730-737
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• 2018

With the increasing number of health consumers aiming for a happy quality of life, the O2O medical marketing market is activated by choosing reliable health care facilities and receiving high quality medical services based on the medical information distributed on web's blog. Because unstructured text data used on the Internet, mobile, and social networks directly or indirectly reflects authors' interests, preferences, and expectations in addition to their expertise, it is difficult to guarantee credibility of medical information. In this study, we propose a blog reading system that provides users with a higher quality medical information service by classifying medical information blogs (medical blog, ad blog) using bigdata and MLP processing. We collect and analyze many domestic medical information blogs on the Internet based on the proposed big data and machine learning technology, and develop a personalized health information recommendation system for each disease. It is expected that the user will be able to maintain his / her health condition by continuously checking his / her health problems and taking the most appropriate measures.

• The Korean Journal of Archival Studies
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• no.50
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• pp.139-175
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• 2016

This study is a content analysis on the National Archives of Korea as reflected in tweets produced between 2014 and 2015. The study thus collected all tweets that used the key word 'National Archives of Korea' from 2014 and 2015. The contents of the tweets, including their category and issues mention, were then analyzed. The results of the analysis were as follows. First, the analysis showed that the collected archives of the National Archives had increased their volume in over two years, which have a similar type and pattern in their content. Second, the tweets produced by the public reflects more current political and social issues rather than archival service.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.2
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• pp.356-375
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• 2021

The Generation Z (Gen-Z) consumer has a unique beauty-consuming behavior that is distinct from the previous generations. This study aims to identify the meaning of makeup rituals based on the theoretical framework of the ritual concept. In-depth interviews were conducted with fifteen females in their mid-teens to early 20s. The results showed that Gen-Z has different types of makeup ritual scripts for both ordinary days and special days, which are constantly being re-written and revised based on the experience accumulated. In addition, there are various types of ritual artifacts that play an important role in Gen-Z's makeup ritual, and that they provide psychological comfort and satisfaction. The importance of DIY (Do It Yourself), collecting, and independent brands is emphasized. The role of Gen-Z in the makeup ritual was expanding from a creator for her own ritual to a collaborator for peers' rituals, and sometimes the expansion goes beyond the direct relationships to virtual ones through SNS (Social Network Service). The Gen-Z cohort is found to be a member of beauty knowledge network through which they learn, share, and create the know-how and shopping skills.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.447-461
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• 2012

A social network service(SNS) is gaining popularity as a new real-time information sharing mechanism. However, the user's privacy infringement is occurred frequently because the information that is shared through a social network include the private information such as user's identity or lifestyle patterns. To resolve this problem, the research about privacy preserving data sharing in social network are being proceed actively. In this paper, we proposed the efficient scheme for privacy preserving data sharing in social network. The proposed scheme provides an efficient conjunctive keyword search functionality. And, users who granted access right to storage server can store and search data in storage server. Also,, our scheme provide join/revocation functionality suited to the characteristics of a dynamic social network.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.35-44
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• 2020

In this study, we analyze how stock trend determination affects trend prediction accuracy. In stock markets, successful investment requires accurate stock price trend prediction. Therefore, a volume of research has been conducted to improve the trend prediction accuracy. For example, information extracted from SNS (social networking service) and news articles by text mining algorithms is used to enhance the prediction accuracy. Moreover, various machine learning algorithms have been utilized. However, stock trend determination has not been properly analyzed, and conventionally used methods have been employed repeatedly. For this reason, we formulate the trend determination as a moving average-based procedure and analyze its impact on stock trend prediction accuracy. The analysis reveals that trend determination makes prediction accuracy vary as much as 47% and that prediction accuracy is proportional to and inversely proportional to reference window size and target window size, respectively.

• The Journal of Information Systems
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• v.31 no.1
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• pp.289-304
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• 2022

Purpose The development of the network and mobile industries has induced companies to invest in information systems, leading a new industrial revolution. The Journal of Information Systems, which developed the information system field into a theoretical and practical study in the 1990s, retains a 30-year history of information systems. This study aims to identify academic values and research trends of JIS by analyzing the trends. Design/methodology/approach This study aims to analyze the trend of JIS by compounding various methods, named as TLS mining analysis. TLS mining analysis consists of a series of analysis including Term Frequency-Inverse Document Frequency (TF-IDF) weight model, Latent Dirichlet Allocation (LDA) topic modeling, and a text mining with Semantic Network Analysis. Firstly, keywords are extracted from the research data using the TF-IDF weight model, and after that, topic modeling is performed using the Latent Dirichlet Allocation (LDA) algorithm to identify issue keywords. Findings The current study used the summery service of the published research paper provided by Korea Citation Index to analyze JIS. 714 papers that were published from 2002 to 2012 were divided into two periods: 2002-2011 and 2012-2021. In the first period (2002-2011), the research trend in the information system field had focused on E-business strategies as most of the companies adopted online business models. In the second period (2012-2021), data-based information technology and new industrial revolution technologies such as artificial intelligence, SNS, and mobile had been the main research issues in the information system field. In addition, keywords for improving the JIS citation index were presented.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.5
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• pp.37-48
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• 2022

With development of Digital Technology, social issues are communicated through digital-based platform such as SNS and form public opinion. This study attempted to analyze big data from Twitter, a world-renowned social network service, and find out the public opinion. After collecting Twitter data based on 14 keywords for 1 year in 2021, analyzed the term-frequency and relationship among keyword documents with pearson correlation coefficient using Data-mining Technology. Furthermore, the 6 main topics that on the center of information security field in 2021 were derived through topic modeling using the LDA(Latent Dirichlet Allocation) technique. These results are expected to be used as basic data especially finding key agenda when establishing strategies for the next step related industries or establishing government policies.

• Annual Conference of KIPS
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• 2010.11a
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• pp.1478-1481
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• 2010

기존의 테마파크에 RFID를 이용하면 보다 편리하게 출입관리를 할 수 있고, 카드 한 장으로 테마파크 내에서 결제부터 부대시설과 서비스까지 이용할 수 있다. 이러한 모델은 이미 서브원 곤지암리조트 스키장과 캐리비언베이 워터파크 등 에서 도입하여 사용하고 있다[1][2]. 그러나 RFID를 이용한 유비쿼터스 모델들의 공통적인 단점은 RFID 카드 사용에 대한 피드백을 받을 수 없다는 것이다. 다시 말해서 RFID 카드에 대한 정보를 사용자는 모르기 때문에 자신이 RFID 카드로 무엇을 얼마나 결제했는지, 어떠한 서비스를 사용했는지 다시 확인할 수 없다는 문제점이 있다. 본 논문에서는 이러한 기존의 시스템에 스마트폰을 이용하여 사용자와 테마파크를 유기적으로 연결시켜줌으로써, 스마트폰을 통해 자신의 결제정보, 서비스 이용내역 등을 실시간으로 확인 가능할 수 있는 u-테마파크 모델을 제시한다. u-테마파크 모델을 이용하면 스마트폰을 통해 부대시설(놀이공원의 놀이기구, 스키장의 리프트 등)의 대기시간을 실시간으로 확인할 수 있고, RFID 카드를 소지한 일행의 위치를 찾을 수 있으며, 테마파크의 모든 이용객들과 정보를 교환할 수 있는 SNS(Social Network Service)등의 새로운 서비스를 제공할 수 있다. 테마파크 측에서는 실시간으로 취합되는 고객정보를 이용하여 이용률이 떨어지는 고객들의 특징을 파악해 해당 고객들에게 맞는 서비스를 제공하고 맞춤 마케팅을 하는 등의 체계적인 관리를 할 수 있어 다양한 마케팅과 새로운 서비스 제공이 가능하다는 이점이 있다.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.2
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• pp.17-29
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• 2023

The digital environment, which has been rapidly developing since the beginning of the 21^st century, has become more specific due to COVID-19, and marketing strategies are rapidly changing to suit purchasing activities of Generation MZ, whose online purchases are becoming the center of their lives. A public relations agency is generally responsible for all aspects of making a client's product or service visible to the public through various forms of media. Among them, a company that performs only fashion-related tasks is called a "fashion PR agency". Now, the fashion industry is also centered on the e-commerce environment, and various digital marketing strategies have been developed and directly related to sales. This study examined the current status of online media and digital marketing, analyzes the aspects of fashion brand promotion strategies and methods in the e-commerce era, focusing on the work of fashion PR agencies, and suggests the direction of new online and offline promotion methods based on marketing and technological aspects. As a result of the study, first, theories on strategies for online media and digital marketing were examined, and found that the amount of online promotion has recently increased and become more specialized. Second, this study examines the concept of fashion PR agencies and analyzed their main tasks through interviews with fashion PR professionals. Third, based on successful online fashion promotion cases, the study analyzed fashion promotion strategies and methods that are being integrated online and offline in the e-commerce era. The main methods included SNS strategy, content strategy, performance strategy, influencer strategy, and event strategy, and it is suggested that integrated management is necessary for consistent brand image management, and an IMC (Integrated Marketing Communication) strategy, which intensively manages all strategies, should be employed.