• Journal of Digital Convergence
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• v.16 no.10
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• pp.399-407
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• 2018

The influence of SNS platform in the mobile environment has grown greatly. Among the various social networking services(SNS), this study analyzed the question of 311 women to investigate whether any difference exists between reliability of contents information, informativeness and playfulness as well as how attributes of contents information influence user attitude depending on the difference in type of providing information provided by "Innisfree" Cosmetics, the company account of Instagram. According to analysis, first, no difference exists between reliability of contents information, informativeness and playfulness depending on the type of providing information. Second, reliability and the playfulness of contents information influence purchase intention. Third, contents information "informativeness" and "playfulness" influence loyalty. Fourth, the "informativeness" and "playfulness" of contents information influence User Satisfaction. Considering such result, it is confirmed that the type of providing information provided by company does not influence account attributes and the "playfulness" of contents information is significant factor which influences all user attitude.

• Journal of Distribution Science
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• v.14 no.9
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• pp.85-94
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• 2016

Purpose - Recently, Mobile technologies and devices including smart phones and tablets have increased the possibility of communicating with other people and sharing personal information without time and space restriction. In order to realize the market potential related to mobile technologies, a large number of internet services have been incorporated into mobile platforms. Especially, The number of MIM(Mobile Instant Messenger) users has been increasing dramatically and services using MIM platform also have diversified. In spite of drastic growth in markets related to MIM, there is little empirical research on MIM and users' behaviors. This study designed to examine the structural relationships among belongingness, loneliness, self-disclosure intention, system quality, and self-disclosure behavior in context of MIM. Research design, data, and methodology - Three hypotheses were about the relationship among belongingness, loneliness and self-disclosure intention. The other two hypotheses were about the moderating effect of system quality in the causal relationship between self-disclosure intention and self-disclosure behavior. The data was analyzed by structural equation modeling. Research data were obtained from 330 undergraduate students who were KakaoTalk users and total 314 valid questionnaires were used in the final analysis. Results - The results from this study are as follow. First, the belongingness and the loneliness had a significant impact on self-disclosure intention in MIM. Second, the self-disclosure intention in MIM also had a positive impact on the self-disclosure behavior. Lastly, there is a moderating effect of the system quality in the relationship between the self-disclosure intention and self-disclosure behavior in MIM. Specifically, the higher system quality level was perceived, the positive effect of the self-disclosure intention in MIM on the self-disclosure behavior was greater. Conclusions - Based on the results from this study, academic and practical implications can be drawn. First, the study extends the scope of research about SNS through focusing on MIM to be classified by closed type SNS and identifies the relationship between emotion, behavioral intention and behaviors in MIM. Second, this study provides strategic guidelines to increase the efficiency for promotion activity. Limitations for the study also should be discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1551-1559
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• 2015

Recently, the performance of smart devices is almost similar to that of the existing PCs, thus the users of smart devices can perform similar works such as messengers, SNSs(Social Network Services), smart banking, etc. originally performed in PC environment using smart devices. Although the development of smart devices has led to positive impacts, it has caused negative changes such as an increase in security threat aimed at mobile environment. Specifically, the threats of mobile devices, such as leaking private information, generating unfair billing and performing DDoS(Distributed Denial of Service) attacks has continuously increased. Over 80% of the mobile devices use android platform, thus, the number of damage caused by mobile malware in android platform is also increasing. In this paper, we propose android based malware detection mechanism using time-series analysis, which is one of statistical-based detection methods.We use auto-regressive moving-average model which is extracting accurate predictive values based on existing data among time-series model. We also use fast and exact malware detection method by extracting possible malware data through Z-Score. We validate the proposed methods through the experiment results.

• Informatization Policy
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• v.30 no.3
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• pp.3-28
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• 2023

This study aims to analyze the usage behavior of e-government service users based on the e-government maturity model and provide suggestions for advancement of the e-government services. The changes in Korea's e-government services were analyzed as follows; 1) Proportion of use of e-government services in Korean public services, 2) E-government service types/stages use, 3) Service use by platform 4) User response to e-government service 5) Users' requests for future e-government service usage methods. For the analysis, this study used data from Korea's 2012-2020 e-government usage behavior survey data. As a result of the analysis, first, the proportion of e-government service has been continuously increasing, and second, the use of the e-participation stage is relatively low compared to the presenting information, interaction, and transaction stages. Third, by platform, e-government service has been expanded to various access platforms such as mobile, kiosk, and SNS centering on the web. Fourth, users' satisfaction with e-government service is very high. However, to vitalize e-government services, users requested improvements such as providing one-stop integrated services and simplifying authentication procedures. Based on the analysis results, this study 1) reflects the user's point of view in the maturity model of e-government, 2) considers access to various platforms according to the development of digital technology, 3) improves the e-government maturity model through data-based analysis such as user usage behavior suggested the need.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.6
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• pp.1293-1300
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• 2012

With the rapid evolution of mobile devices and the development of wireless networks, users of mobile social network service on smartphone have been increasing. Also the security of personal information as a result of real-time communication and information-sharing are becoming a serious social issue. In this paper, a framework that can be linked with a social network services platform is designed using OpenAPI. In addition, we propose an authentication and detection mechanism to enhance the level of personal information security. The authentication scheme is based on an user ID and password, while the detection scheme analyzes user-designated input patterns to verify in advance whether personal information protection guidelines are met, enhancing the level of personal information security in a social network service environment. The effectiveness and validity of this study were confirmed through performance evaluations at the end.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.125-149
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• 2012

As the smart phone is propagating rapidly, the importance of mobile advertisement has also grown. One of the main characteristics of the Internet and smart phone advertising is that they can deliver personalized advertisements to each customer. The smart phone enables the identification of additional personalized information such as the customer's location and the accessibility to the site at any place any time. As the Internet platform becomes richer, firms that offer the ad services via the wired PC Internet and wireless smart phone are seeking various types of personalized ads. However, their service platform and Information and Communication Technology (ICT) platform should be suitable to the characteristics of personalized ads. This research explores various types of personalized ad methods and evaluates their adequacy encompassing four types of ad service platforms (such as search portal, news portal, e-mall servers, and SNS) and two types of ICT platforms (PC Internet and smart phone). To this end, we classified the personalized ads into seven types: three basic types and four composite types. The basic types of ad methods are identified by considering the current activity that the customer is engaged, the individual profile and log history, and the customer's current location or planning location. Four composite types of ad methods are constructed as the combination of these basic types. For those types of ad methods, we evaluate whether each ad method adequately maps with four types of ad service platforms and two types of ICT platforms. We proposed a metric of evaluation and demonstrated the concept with illustrative numbers. Specifically, we analyze and compare personalized ad methods in three ways. Firstly, the possibility of implementing a personalized ad method on the platform is analyzed to confirm the degree of suitability. Secondly, the value of personalized ad method is analyzed based on the customer accessibility. Lastly, expected effectiveness for each personalized ad method is computed by multiplying the possibility and the value. Through this kind of analysis, the ad service providers as well as advertising companies can evaluate what kinds of personalized ad methods and platforms are possible and suitable to maximize their ad effectiveness on the Internet and smart phone platforms.

• Journal of Korean Dental Hygiene Science
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• v.5 no.2
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• pp.97-104
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• 2022

Background: Due to the declining number of students preparing for university entrance exams , the quota of universities has been decreasing continuously. This situation became increasingly diverse as new media used online, mobile, and PR tools to continuously invite students. This study is aimed at offering the helpful data to plan an effective PR strategy by analyzing the correlation between the major selection and satisfaction of the department's social media usage among freshmen majoring in dental hygiene. Methods: The collected data from the self-reported survey with freshmen were analyzed using the SPSS 22.0 program. The survey items were motive to select the major, social media platform that subjects used, reasons to use the media, time to visit the department's social media platform, and satisfaction level on the department's social media platform, using a 5-point Likert Scale. Results: The reasons for choosing a major were given by 32.2% and 15.9% respondents, respectively, as the vision after graduation and practice facilities. 39.9% and 31.4% used Instagram and YouTube for social media platforms, respectively, for using social media platform; 26.9% and 26.3% visited the department's social media before and after entering the university, respectively; 46.4% and 24.9% used Instagram and YouTube for department social media; and they generally satisfied with the contents of the department's social media. 40.9% of them said that information from the department's social media was useful. 33.8% of them said the information from the department's social media exceeded their expectations. 46.8% of them answered that the department's social media made the department's image positive. 33.4% got interested in the major more due to the department's social media. According to 32.1% of respondents, the department's social media was helpful in deciding on a major. With 35.4%, a positive correlation was discovered between the department's practice facilities and satisfaction on the department's social media. Conclusion: It is thought that the department's social media should try continuously by uploading the contents to meet the users' needs on a regular basis and seeking the plans to be able to collect various opinions using surveys through the related social media so that students can select the major and, moreover, lead the positive direction to adapt the university life under the unfamiliar environment after admission.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.405-411
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• 2019

The purpose of the study is to investigate a usability of using fashion and beauty service and suggest better user experience on Instagram's newly released mobile video platform, IGTV. The study expects to be a resource of improving the usability on fashion and beauty contents on IGTV and encourage further research for suggesting better guidelines. As a research method, it will experiment current mobile video service first with literature review. Afterwards, the research conducted tasks and in-depth interview with eight Instagram users to evaluate a usability of using fashion and beauty service on IGTV. As a result, it is able to derive two plans that needed improvement. Firstly, IGTV is required to have high accessibility for user's to use service longer and intuitive user experience. Secondly, unlike previous service that Instagram have offered, IGTV need to differentiate to share and get information of fashion and beauty trends.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.465-467
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• 2022

Mobile phones have become an essential item nowadays since it provides access to online platform and service fast and easy. Coming to these platforms such as Social Network Service (SNS) for shopping have been a go-to option for many people. However, searching for a specific fashion item in the picture is challenging, where users need to try multiple searches by combining appropriate search keywords. To tackle this problem, we propose a system that could provide immediate access to websites related to fashion items. In the framework, we also propose a deep learning model for an automatic analysis of image contexts using instance segmentation. We use transfer learning by utilizing Deep fashion 2 to maximize our model accuracy. After segmenting all the fashion item objects in the image, the related search information is retrieved when the object is clicked. Furthermore, we successfully deploy our system so that it could be assessable using any web browser. We prove that deep learning could be a promising tool not only for scientific purpose but also applicable to commercial shopping.