• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.499-510
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• 2012

An SNS(Social Network Service) is an online service that supports an effective way to share information over virtual communities. Recently, as SNSs such as Twitter, Facebook, and Me2day are getting bigger, the purposes of using popular SNSs are expanded to broadcastings, politics, marketings and so on. In this paper, we propose an API to integrate and manage open APIs for various SNSs, presenting a library as an implementation of the proposed API. Also, utilizing the developed library, a smartphone application is provided which supports integrated management of popular SNSs and personal schedules. Using the library, developers can reduce costs when they need to implement specific functions for managing various SNSs. With the developed application, we can read and write to/from the related SNSs on same screen, automatically reminding our schedule and sharing the schedule with friends over the SNSs.

• Journal of Digital Contents Society
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• v.16 no.3
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• pp.471-482
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• 2015

Recently commercialized network are getting more and more popular, bringing dramatic change to the market. We can predict the future of the E-commerce. The ongoing E-commerce and SNS （Social Networking Services）related E-commerce are increasing greatly both in Korea and China. This research tries to focus on Chinese consumers using E-commerce. The study has four findings. Firstly, the E-commerce consumers consider four factors including price, convenience, products and website, which affect the sellers' integrity. Secondly, E-commerce will affect sellers' integrity. Third, there are 4 factors which affect the sellers' integrity: service, price, products and the information. Fourth, the factors which affect the integrity of sellers are the value, happiness and practical. This study want to give some hints to the E-commerce in the overseas market in China.

• The KIPS Transactions:PartD
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• v.19D no.4
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• pp.271-280
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• 2012

Currently, contents generated by SNS services are increasing exponentially, as the number of SNS users increase. The SNS is commonly used to post personal status and individual interests. Also, the SNS is applied in socialization, entertainment, product marketing, news sharing, and single person journalism. As SNS services became available on smart phones, the users of SNS services can generate and spread the social issues and controversies faster than the traditional media. The existing indexing methods for web contents have limitation in terms of real-time indexing for SNS contents, as they usually focus on diversity and accuracy of indexing. To overcome this problem, there are real-time indexing techniques based on RDBMSs. However, these techniques suffer from complex indexing procedures and reduced indexing targets. In this regard, we introduce the TK-Indexing method to improve the previous indexing techniques. Our method indexes the generation time of SNS contents and keywords by way of NoSQL to indexing SNS contents in real-time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.10
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• pp.908-917
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• 2013

In this paper, we propose a discovery protocol for finding nearby mobile applications and services in a device-to-device communications system. The device-to-device communication technology enables proximity-based services such as mobile social networks and mobile marketing. For realizing these proximity-based services, it is essential to design a discovery protocol which pinpoints the devices with mobile applications of interest among hundreds and thousands of devices in proximity. In the infrastructure-less networks such as ad hoc networks, we can design the discovery protocol that periodically broadcasts a short discovery code containing the compressed information of the mobile applications. In this paper, we design the discovery protocol with the discovery code generated by using a hash function and a Bloom filter. We also mathematically analyze the performance of the proposed protocol.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.2
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• pp.33-40
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• 2016

Due to the growth of social network systems (SNS), big data are realized and Hadoop was developed as a distributed platform for analyzing big data. Enterprises analyze data containing users' sensitive information by using Hadoop and utilize them for marketing. Therefore, researches on data encryption have been done to protect the leakage of sensitive data stored in Hadoop. However, the existing researches support only the AES encryption algorithm, the international standard of data encryption. Meanwhile, Korean government choose ARIA algorithm as a standard data encryption one. In this paper, we propose a HDFS data encryption scheme using ARIA algorithms on Hadoop. First, the proposed scheme provide a HDFS block splitting component which performs ARIA encryption and decryption under the distributed computing environment of Hadoop. Second, the proposed scheme also provide a variable-length data processing component which performs encryption and decryption by adding dummy data, in case when the last block of data does not contains 128 bit data. Finally, we show from performance analysis that our proposed scheme can be effectively used for both text string processing applications and science data analysis applications.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.75-84
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• 2019

The purpose of this paper is to examine the factors influencing on loyalty in US online shopping malls. The study proposed a model to investigate the relationship among quality of sites, satisfaction, attitude, and loyalty. The hypotheses were examined by analyzing a structural equation model. 280 US samples were used for the final analysis. The results show that this model demonstrates good fit for the samples. The ease of use was found to be a significant variable in their satisfaction, while it did not have the direct effect on attitude toward the sites. The information quality was found to be a crucial variable in consumers' satisfaction and attitude toward the site. Satisfaction directly affected attitude as well as loyalty, and attitude also directly affected loyalty. Thus, the structural relationship among the variables of customers' loyalty was verified. This research provides practical insights into US consumer behaviors that would be beneficial to marketers when they make decisions for the US e-commerce market.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.61-81
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• 2021

In the era of untact, the "Chabak" using cars as accommodation spaces is attracting attention as a new form of travel. Due to the advantages, including low costs, convenience, and safety, as well as the characteristics of the vehicle enabling independent travel, the demand for Chabak is continuously increasing. Despite the rapid growth of the market and related industries, little academic has investigated this trend. To establish itself as a new type of travel culture and to sustain the growth of related industries, it is essential to understand the public perception of Chabak. Therefore, based on the marketing mix theory and big data analysis, this study analyzes the public perception of Chabak. The results showed that Chabak has established itself as a consumer-led travel culture, contributing to the aftermarket growth of the automobile industry. Additionally, consumers were found to be increasingly inclined to enjoy travel economically and wisely, and actively share information through social media. This initial study on the new travel trend of Chabak is significant in that it employs big data analysis on a theoretical basis.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.642-657
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• 2022

The fourth industrial revolution became a decisive opportunity to increase our dependence on non-face-to-face services. Therefore, this study tried to derive a new strategic plan for non-face-to-face marketing by discussing the short-form branded content currently in the spotlight among the digital native generation. In particular, focusing on the phenomenon of co-viewing, where short-form branded content is viewed and communicated on social media, how exposure type of branded content affect attitudes toward short-form branded content and the products it contains verified. In addition, this research presents the perceived sense of belonging as a mediating variable. It was confirmed through an experiment whether the sense of belonging perceived by consumers during the co-viewing process significantly mediated the relationship between the exposure types and consumer attitudes. As a result of the study, it was found that the exposure type significantly affected the attitude towards the contents and the products contained in them. Furthermore, the perceived sense of belonging was also significant as a mediating variable.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.477-488
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• 2022

The purpose of this study is to examine how factors that select Airbnb service affect service satisfaction and the moderating effect according to marital status. The subjects of this study are customers who who have used Airbnb services in the metropolitan area. The questionnaire survey was conducted with 150 people, and the results were analyzed and hypothesis testing was performed using Structural Equation Model(SEM). As a result of the study, it has been found that price, online review, and Unique Experience Expectation(UEE) among the factors that selected Airbnb have positive effects on service use satisfaction. In addition, marital status has been found to play a mediating role among price, UEE and customer satisfaction. For single customers, price is an important factor influencing service satisfaction, but for married customers, it is not. In this sense, it is important not only to conduct marketing and promotions considering only gender, but also to provide services according to whether they are single or married.

• Journal of Industrial Convergence
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• v.22 no.3
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• pp.13-25
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• 2024

This study explores research topics related to dance performances published in Korea based on big data and examines research trends that change according to the trend of the times. The results derived from topic modeling analysis are as follows. (1) Six major topics were derived: a study on marketing strategies and development plans for dance performances, (2) a study on the re-watching factors of dance performance space and performance satisfaction, (3) a study on the popularity and contribution of dance performances in the stage environment, (4) a study on the current status of dance performances and the convergence of dance group operations, (5) a study on the definition of dance performances using various social media, and (6) a study on the direction and development of technology-applied dance performance contents. Accordingly, research trends and topics related to dance, including dance performances, social changes, key keywords of researchers' change interests were extracted, and keywords were compared and analyzed to present academic changes and countermeasures. Accordingly, the need for research to apply new technologies was emphasized as it diversified and fused.