• 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.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.417-422
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• 2016

Rapid growth of internet utilization consequences in an expansion of individual's social networks via SNS. Recently, Facebook has added six different emotion buttons reflecting suggestions claiming that "Like" button is limited, and thus must be improved. Regarding to how well newly updated six different emotion buttons were utilized, a survey that inquires the usefulness and usability of buttons for further improvement in service was conducted to 35 Facebook users of 20's and 30's, the most active ages with frequent usages. As a result, users responded with negative attitudes considering expression of six different emotions in Facebook, and exhibited less frequent usages of the service. According to respondents, the emotion expression service would lead better approachability if Facebook suggests simpler emotion expression, for example, two emotion buttons rather than current six buttons.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.754-764
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• 2016

To understand and analyze SNS(Social Network Service) two important classes of networks, small-world and scale-free networks have gained a lot of research interests. In this study, a generalized network generation method is developed, which can produce small-world network, scale-free network, or network with the properties of both small-world and scale-free by controlling two input parameters. By tuning one parameter we can represent the small-world property and by tuning the other one we can represent both scale-free and small-world properties. For the network measures to represent small-world and scale-free properties clustering coefficient, average shortest path distance and power-law property are used. Using the model proposed in this study we can have more clear understanding about relationships between small-world network and scale-free network. Using numerical examples we have verified the effects of two parameters on clustering coefficient, average shortest path distance and power-law property. Through this investigation it can be shown that small-world network, scale-free network or both can be generated by tuning two input parameters properly.

• 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.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.622-635
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• 2018

On top of presenting the possibility of expanding the game space to social space through mobile communication, MSNG reinforces the strengths of SNS and the fun of games through closer networks between users. This study empirically verified the effects of the characteristics of MSNG on interactions and user satisfaction by dividing the main characteristics of MSNG into graphics, challenge spirit, and reward, and then dividing the main characteristics of mobile social network service into social interaction and technical interaction. In the results of study, the main characteristics of MSNG such as graphics, challenge spirit, and reward all had significant effects on the social interaction and technical interaction while the social interaction and technical interaction of MSNG also had significant effects on the user satisfaction, so that the hypotheses of this study were all selected. The influence of the characteristics of MSNG on interactions might be because of shared feedbacks through graphics, game tasks, and reward in the performance process of MSNG, and such interactions make diverse people have the horizontal or circular communication, which is led to the increase of user satisfaction.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.377-379
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• 2022

POI refers to the point of Interest in Location-Based Social Networks (LBSNs). With the rapid development of mobile devices, GPS, and the Web (web2.0 and 3.0), LBSNs have attracted many users to share their information, physical location (real-time location), and interesting places. The tremendous demand of the user in LBSNs leads the recommendation systems (RSs) to become more widespread attention. Recommendation systems assist users in discovering interesting local attractions or facilities and help social network service (SNS) providers based on user locations. Therefore, it plays a vital role in LBSNs, namely POI recommendation system. In the machine learning model, most of the training data are stored in the centralized data storage, so information that belongs to the user will store in the centralized storage, and users may face privacy issues. Moreover, sharing the information may have safety concerns because of uploading or sharing their real-time location with others through social network media. According to the privacy concern issue, the paper proposes a recommendation model to prevent user privacy and eliminate traditional RS problems such as cold-start and data sparsity.

• Journal of Information Technology and Architecture
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• v.11 no.1
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• pp.33-44
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• 2014

Recently, blogs have attracted much attention as personal media. The power of blogs as a way to provide valuable resources on Internet is so tremendous because of the high speed of information dissemination and the huge influence of the circulated information on Internet users even when the information itself is not true. Especially, contents on blogs that attract a lot of public attention are sometimes reproduced or magnified in an inappropriate way. In this paper, a method to measure the trust level of contents posted on personal blogs is proposed to reduce the damage of wrong information circulated along with blog networks. Trust variables such as relationship data in SNS are used to measure the comparative trust level of blog contents. The structure of the prototype system is also designed to apply this framework to blogsphere.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.57-79
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• 2016

It is a rising trend that the number of users using one of the social media channels, the Social Network Service, so called the SNS, is getting increased. As per to this social trend, more companies have interest in this networking platform and start to invest their funds in it. It has received much attention as a tool spreading and expanding the message that a company wants to deliver to its customers and has been recognized as an important channel in terms of the relationship marketing with them. The environment of media that is radically changing these days makes possible for companies to approach their customers in various ways. Particularly, the social network service, which has been developed rapidly, provides the environment that customers can freely talk about products. For companies, it also works as a channel that gives customized information to customers. To succeed in the online environment, companies need to not only build the relationship between companies and customers but focus on the relationship between customers as well. In response to the online environment with the continuous development of technology, companies have tirelessly made the novel marketing strategy. Especially, as the one-to-one marketing to customers become available, it is more important for companies to maintain the relationship marketing with their customers. Among many SNS, Facebook, which many companies use as a communication channel, provides a fan page service for each company that supports its business. Facebook fan page is the platform that the event, information and announcement can be shared with customers using texts, videos, and pictures. Companies open their own fan pages in order to inform their companies and businesses. Such page functions as the websites of companies and has a characteristic of their brand communities such as blogs as well. As Facebook has become the major communication medium with customers, companies recognize its importance as the effective marketing channel, but they still need to investigate their business performances by using Facebook. Although there are infinite potentials in Facebook fan page that even has a function as a community between users, which other platforms do not, it is incomplete to regard companies' Facebook fan pages as communities and analyze them. In this study, it explores the relationship among customers through the network of the Facebook fan page users. The previous studies on a company's Facebook fan page were focused on finding out the effective operational direction by analyzing the use state of the company. However, in this study, it draws out the structural variable of the network, which customer committment can be measured by applying the social network analysis methodology and investigates the influence of the structural characteristics of network on the business performance of companies in an empirical way. Through each company's Facebook fan page, the network of users who engaged in the communication with each company is exploited and it is the one-mode undirected binary network that respectively regards users and the relationship of them in terms of their marketing activities as the node and link. In this network, it draws out the structural variable of network that can explain the customer commitment, who pressed "like," made comments and shared the Facebook marketing message, of each company by calculating density, global clustering coefficient, mean geodesic distance, diameter. By exploiting companies' historical performance such as net income and Tobin's Q indicator as the result variables, this study investigates influence on companies' business performances. For this purpose, it collects the network data on the subjects of 54 companies among KOSPI-listed companies, which have posted more than 100 articles on their Facebook fan pages during the data collection period. Then it draws out the network indicator of each company. The indicator related to companies' performances is calculated, based on the posted value on DART website of the Financial Supervisory Service. From the academic perspective, this study suggests a new approach through the social network analysis methodology to researchers who attempt to study the business-purpose utilization of the social media channel. From the practical perspective, this study proposes the more substantive marketing performance measurements to companies performing marketing activities through the social media and it is expected that it will bring a foundation of establishing smart business strategies by using the network indicators.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.341-348
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• 2014

The advance in web accessibility with dissemination of smart phones gives rise to rapid increment of users on social network platforms. Many research projects are in progress to detect events using Twitter because it has a powerful influence on the dissemination of information with its open networks, and it is the representative service which generates more than 500 million Tweets a day in average; however, existing studies to detect events has been used TFIDF algorithm without any consideration of the various conditions of tweets. In addition, some of them detected predefined events. In this paper, we propose the RTFIDF VT algorithm which is a modified algorithm of TFIDF by reflecting features of Twitter. We also verified the optimal section of TF and DF for detecting events through the experiment. Finally, we suggest a system that extracts result-sets of places and related keywords at the given specific time using the RTFIDF VT algorithm and validated section of TF and DF.

• 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.