• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.139-157
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• 2019

This study is intended for demonstrating the impacts of different factors on the formation of online consumer engagement behavior of young Chinese moviegoer in Korea. Based on Value-Exchange Model [Itani et al., 2019], we build research model to reveal the relationships among perceived enjoyment, perceived movie information value, multiplex-audience relationship quality, multiplex usage satisfaction, and online consumer engagement through experiments on valid data we collected from 186 participants who had lived in Korea and experienced the multiplex pages of top 3 movie theaters, where Smart PLS 3.0 is the tool used for statistical analysis. The experimental results show that both perceived enjoyment and perceived movie information value positively correlate to multiplex-audience relationship quality, and multiplex audience relationship quality significantly influences multiplex usage satisfaction and online consumer engagement. In addition, it is found that relationship quality plays the role of mediator between perceived enjoyment and satisfaction. The findings from this study offer both academic and managerial implications for movie distributors who are interested in developing potential Chinese consumer market in Korea.

• Journal of Service Research and Studies
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• v.12 no.3
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• pp.144-157
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• 2022

This study began by pointing out the problem of domestic media reporting on 'fake news' regulations that frequently appear through the French 'Les proposals de loi control de l'information'case, while still approaching with different standards and perspectives on where to see fake news. In the age of 'social network services', the answer to what the media is, what the news is, and who the reporter is increasingly difficult. While reviewing the long history and background of the spread of fake news examined in this study, it was confirmed that could not determine the concept and scope of fake news, punished, regulated, controlled, or judged simply by one standard. From the perspective of 'freedom of expression' set by the law, we have the authority to express our opinions freely. In addition, 'online' space is a place where fake news is generated and spread, but at the same time, there is plenty of room to act as an antidote. In the end, the only alternative to the damage of long-term fake news will be to create a media environment that allows more high-quality "real news" to pour out, allowing us to develop our ability to judge reliable information through balanced competition among various news in the free market of ideas.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.93-103
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• 2021

The special means of transportation introduced to improve the mobility of the transportation vulnerable met the number of legal standards in 2016, but lack of development in terms of quality, such as the existence of long waiting times. In order to streamline the operation of special means of transportation, long-term standby traffic, which is the top 25% of the wait time, was extracted from the Daegu Metropolitan Government's special transportation history data, and spatial autocorrelation analysis and social network analysis were conducted. As a result of the analysis, the correlation between the average waiting time of special transportation users and the space was high. As a result of the analysis of internal degree centrality, the peak time zone is mainly visited by general hospitals, while the off-peak time zone shows high long-term waiting demand for visits by lawmakers. The analysis of external degree centrality showed that residential-based traffic demand was high in both peak and off-peak hours. The results of this study are considered to contribute to the improvement of the quality of the operation of special transportation means, and the academic implications and limitations of the study are also presented.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.177-178
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• 2019

본 연구에서는 SNS 품질요인에 대한 기존 연구에 대해 전문가 집단이 산출한 각 품질요인에 대한 중요도와 사용자 집단이 각 품질요인에 대해 중요하다고 생각하는 중요도의 차이를 알아보고자 하였다. 연구를 위하여 선행연구에서 사용된 SNS 품질요인을 시스템품질, 정보품질, 인터페이스품질, 서비스품질로 구분하여 AHP 기법을 적용하여 전문가 집단과 사용자 집단의 품질요인별 중요도를 실증 분석하였다. 분석결과 전문가 집단과 사용자 집단의 각 품질요인에 대한 중요도의 인식 차이가 나타나는 것으로 나타나 품질평가에 있어 전문가와 사용자의 의견을 종합하는 종합 평가가 필요할 것으로 사료된다.

• Human Ecology Research
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• v.57 no.2
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• pp.171-183
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• 2019

Convergence between technology and financial services is ubiquitous and widespread. Virtual banks represent an important aspect of financial markets that can generate value added for consumers and enhance the quality of financial services. This study explores the effect of innovation characteristics (relative advantage, compatibility, and perceived risk), consumer characteristics (status quo bias), and social mechanisms (network externality: complementarity, numbers of peers) on consumers' adoption intention and resistance to virtual banks. This study adopted an innovation resistance model with two dependent variables: adoption intention and resistance to virtual banks. An online self-administered survey was conducted and 532 or non-users of virtual banks aged 20 to 69 years old were analyzed. Frequency analysis, descriptive analysis, and hierarchical multiple regression indicated that status quo bias, relative advantage, perceived risk, complementarity, and number of peers insignificantly influence the adoption intention regarding virtual banks. Furthermore, status quo bias, relative advantage, perceived risk, and number of peers insignificantly influence the resistance to virtual banks. Female respondents have a lower adoption intention and higher resistance to virtual banks than male respondents. The findings suggest that the innovation resistance model can be useful in understanding consumers'adoption and resistance behavior as well as reveal that innovation characteristics, consumer characteristics, and social mechanism are important antecedent variables of the innovation adoption decision.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.289-301
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• 2023

Due to the development and dissemination of modern technology, anyone can easily communicate using services such as social network service (SNS) through a personal computer (PC) or smartphone. The development of these technologies has caused many beneficial effects. At the same time, bad effects also occurred, one of which was the spam problem. Spam refers to unwanted or rejected information received by unspecified users. The continuous exposure of such information to service users creates inconvenience in the user's use of the service, and if filtering is not performed correctly, the quality of service deteriorates. Recently, spammers are creating more malicious spam by distorting the image of spam text so that optical character recognition (OCR)-based spam filters cannot easily detect it. Fortunately, the level of transformation of image spam circulated on social media is not serious yet. However, in the mail system, spammers (the person who sends spam) showed various modifications to the spam image for neutralizing OCR, and therefore, the same situation can happen with spam images on social media. Spammers have been shown to interfere with OCR reading through geometric transformations such as image distortion, noise addition, and blurring. Various techniques have been studied to filter image spam, but at the same time, methods of interfering with image spam identification using obfuscated images are also continuously developing. In this paper, we propose a deep learning-based spam image detection model to improve the existing OCR-based spam image detection performance and compensate for vulnerabilities. The proposed model extracts text features and image features from the image using four sub-models. First, the OCR-based text model extracts the text-related features, whether the image contains spam words, and the word embedding vector from the input image. Then, the convolution neural network-based image model extracts image obfuscation and image feature vectors from the input image. The extracted feature is determined whether it is a spam image by the final spam image classifier. As a result of evaluating the F1-score of the proposed model, the performance was about 14 points higher than the OCR-based spam image detection performance.

• The Journal of Industrial Distribution & Business
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• v.11 no.12
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• pp.7-15
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• 2020

Purpose: This study aims to explore the feasibility of expanding complex wards to provide efficient hospital management and high-quality medical services to local residents of Gangneung Medical Center (GMC). Research Design, Data and Methodology: There are four research designs to achieve the research objectives. We analyzed Big Data for 3 months on Social Network Services (SNS). A questionnaire survey conducted on 219 patients visiting the GMC. Surveys of 20 employees of the GMC applied. The feasibility to expand the GMC ward measured through Focus Group Interview by 12 internal and external experts. Data analysis methods derived from various surveys applied with data mining technique, frequency analysis, and Importance-Performance Analysis methods, and IBM SPSS statistical package program applied for data processing. Results: In the result of the big data analysis, the GMC's recognition on SNS is high. 95.9% of the residents and 100.0% of the employees required the need for the complex ward extension. In the analysis of expert opinion, in the future functions of GMC, specialized care (△3.3) and public medicine (△1.4) increased significantly. Conclusion: GMC's complex ward extension is an urgent and indispensable project to provide efficient hospital management and service quality.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.640-645
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• 2014

Many people use social network services as to communicate, to share an information and to build social relationships between others on the Internet. Twitter is such a representative service, where millions of tweets are posted a day and a huge amount of data collection has been being accumulated. Social mining that extracts the meaningful information from the massive data has been intensively studied. Typically, Twitter easily can deliver and retweet the contents using the following-follower relationships. Topic modeling in tweet data is a good tool for issue tracking in social media. To overcome the restrictions of short contents in tweets, we introduce a notion of reply graph which is constructed as a graph structure of which nodes correspond to users and of which edges correspond to existence of reply and retweet messages between the users. The LDA topic model, which is a typical method of topic modeling, is ineffective for short textual data. This paper introduces a topic modeling method that uses reply graph to reduce the number of short documents and to improve the quality of mining results. The proposed model uses the LDA model as the topic modeling framework for tweet issue tracking. Some experimental results of the proposed method are presented for a collection of Twitter data of 7 days.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.135-148
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• 2012

This work is intended to investigate how the factors of enterprise mobile SNS affect user satisfaction and continuous use intention through technology acceptance model proposed by Davis. To achieve the purpose, this researcher explored Information Systems Success model proposed by DeLone & McLean, Technology Acceptance Model proposed by Davis, and Model after Acceptance, and on the basis of the investigation, performed a study. For the data of this work, 9 enterprises, each of which has more than 100 employees and is located in Seoul, were chosen, and a questionnaire survey was conducted on their 276 employees who experienced enterprise mobile SNS. As a data collection tool, a structured self-administered questionnaire was used. For data analysis, SPSS 18.0 and AMOS 18.0 were used for applying Structural Equation modelling. According to the results of this work, three factors of enterprise mobile SNS-systematic factor (system quality, information quality, and service quality), user factor (personal innovation and personal familiarity), social factor (social effects and social interaction)-affected user satisfaction and continuous use intention through perceived availability, perceived easiness, and perceived enjoyment. Also, it was found that the direction of effects matched a theoretical prediction. And, it was revealed that the decision variables and mediating variables significantly affected user satisfaction and continuous use intention. Theoretical and practical meanings were discussed for the study result, and some suggestions were made for the issues of this work and future studies.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.162-162
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• 2019

Water Distribution Network (WDN) is a critical infrastructure to be maintained ensuring proper water supply to wide-spread consumers. The WDN consists of pipes, valves, pumps and tanks, and these elements interact each other to provide adequate system performance. If elements fail by internal or external interruptions, it may result in adverse impact to water service with different degree depending on the failed element. To determine an appropriate maintenance priority, the critical elements need to be identified and mapped in the network. In order to identify and prioritize the critical elements in WDN, an element-based simulation approach is proposed, in which all the elements composing the WDN are reviewed one at a time. The element-based criticality is measured using several resilience indexes that are newly developed in this study. The proposed resilience indexes are used to quantify the impacts of element failure to water service degradation. Here, three resilience indexes are developed, such as User Demand Severity, Economic Value Loss and Water Age Degradation, each of which intends to measure different aspects of consequences, such as social, economic, and water quality, respectively. For demonstration, the proposed approach is applied to a benchmark water network to identify and prioritize the critical elements.