• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.24-38
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• 2018

Since a social networking service (SNS) isconsidered as an effective means to communicate and interact with customers, companies are trying to utilize SNS effectively. There is a lack of theory relating to the attributes of SNS. This study aims to investigate the attributes of SNS to classify SNS. Based on the social network theory, and previous studies on internet, blog, homepage, communication attributes, this study proposes the seven attributes to classify SNS: interaction, communication, entertainment, information, sharing, intimacy and connection. A pre-test, a pilot test and a main test are conducted. In the main test, 239 SNS users are participated. Through a factor analysis this study verifies the seven attributes of SNS. An analysis of variance with multiple comparisons of $Scheff{\acute{e}}$ method identifies that three attributes, interaction, communication and connection, are found to play significant roles to differentiate SNS. Looking at the overall mean values of the SNS by attribute, interaction, sharing, entertainment, intimacy and communication were relatively high in Facebook. Facebook showed higher values in attributes of interaction, sharing, entertainment, intimacy and communication. Twitter shows the relatively high scores for information and connection. Regarding interaction, Facebook shows higher scores than Twitter and Cyworld. For connection, Cyworld showed a significantly lower score than Twitter and Facebook. Cyworld was separated from the others in the light of communication. Cyworld is relatively weak in communication as it is limited to the message exchanges. The results will help in identifying major attributes for each SNS and classifying SNS.

• International Commerce and Information Review
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• v.13 no.4
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• pp.3-21
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• 2011

In this study, several experiments were designed to test the effectiveness of social media in export marketing. In particular, the experiments were made using Twitter and Facebook. The results showed that users' interest were able to increase the effects combined with B2B and B2C marketing events. The B2C marketing events could be made by personal target Event, Poll event, guest comments and social commerce. The B2B marketing was performed using Page Manager, Affiliate page, building and affiliate marketing group. Special features of Facebook such as social plug-in, Twitter integration, and Photo Tagging were found effective. A couple of implications were found in this study. First, the link between social media channel system was key success factor in effective export marketing. Second, the corporate marketing mix and social media consistent with the marketing mix strategy, communication between the managers and the managers' competencies were obtained for the key success factors.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.201-208
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• 2022

Customized service is a vital and mandatory element for apps in improving their technical performance and app customer analysis. While apps require users' consent for their data extraction and usage, many of the terms and agreement forms are written intricately, making it harder for users to fully understand the whole concept of users' data collection for customized services. Ever since the Facebook-Cambridge Analytica scandal, personal data privacy has been re-examined, forcing many app companies to reinforce a reliable solution to data privacy issues. However, there has not been a secured solution, which worries many people about the future advanced issues when metaverse platforms are actively used in daily apps. The research aims to collect the reactions and behaviors of everyday app users who utilize apps with customized services to understand the nature of privacy data issues and the users' opinions about the future implementation of metaverse platforms. The method of the research was an online questionnaire that targeted university students. The study revealed many fearful and anxious reactions about personal data and further metaverse issues where most app users were uneducated about how current apps collect and utilize users' private data.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.6
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• pp.269-276
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• 2015

The today's rapid spread of smartphones makes it easier to use SNS. However, it reveals only their daily life or interest. Therefore, it is hard to really get to know the detailed part of multi-user's common interests. This paper proposes a content recommendation system which recommends people wanted by identifying common interests through SNS. Recommendation system includes proposal formula considering people wanted and deviation in group. After simulation, the proposed system provide high-quality adapted contents to many users by recommendation item according to the common interest. Number of cases about formula are four. It recommend contents that they have many number of 'like' and few number of deviation in users. The proposed system proves by simulations of four cases and read user's 'likes' data. It provide high-quality adapted contents to many users by recommendation item according to the common interest.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.273-280
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• 2014

This study deals with the digital policy proposal through the study about the relation of the sustainable use and the addiction to social media such as facebook. Researcher tried to figure out the antecedents and consequence factors about the service addiction recognized by the social media users and to obtain the measures for the sustainable use of service and the implications for the prevention of addiction. Research results showed that 1) the individual innovation had an effect on the service satisfaction, the addiction, and the sustainable use, 2) the service satisfaction influenced on the addiction and the sustainable use, 3) the perceived service addiction had a reverse effect on the sustainable use. This is described that user's addiction recognition is the obstacle of sustainable growth in service. The proposed policy of this research is summarized as the following two. 1) When the users act the addictive using behavior, service provider has to pay attention to user's withdrawal from the service because of their addiction. 2) The government should offer healing facilities, service etc. for the addicted users and the prevention of the service addiction when they recognized their discomfort.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.5
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• pp.141-148
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• 2011

Recently, various social network services have been grown. Among them, personal relationships based social network services such as Facebook and Twitter make a remarkable growth of industry. In such services, users' profiles are very important for establishing the relationship between two users. However some information in a user's profile causes the leakage of the user's privacy, and thus we have to deal with the information in the profile. Especially, we have to treat contact information, such as the phone number and the e-mail address, very carefully since an adversary can use the information to violate the user's privacy in real life. In this paper, we propose two profile management systems that can enhance the privacy of users in social network services. We compare our systems with existing profile management techniques in well-known social network services such as Facebook and Twitter, and show that our systems provide enhanced privacy.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.145-158
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• 2022

Although the rapid development of technology has led to a swift increase in the number of companies using social networking services (SNS), it will not be accurate to say that they have fully "utilized" the functionality of SNS simply by "using" these services. Therefore, this study aims to increase the convenience of using digital technology and help SNS users in extending the functionality of these services beyond their regular use and thus, revitalize the field by increasing the service providers' efficiency. In this study, the Facebook usage status of a graduate school newspaper from an undisclosed university in Seoul was analyzed from February to December, 2021 using the participant observation method. The results of the study revealed the following: First, it is necessary to diversify the subject and type of content to ensure a continuous supply of quality content; Second, there is a need to examine the user categories and characteristics by utilizing SNS functionalities such as, the target reports and insights, and based on this, supply content that meets the needs of the users; Third, to resolve the problem of low levels of user participation and an inactive Facebook account, it is necessary to mobilize new marketing tools like online events. The significance of this study is that it confronts the real problems faced by some companies that cannot keep pace with market changes in a digital environment, identifies failure factors, and proposes solutions to them.

• Asia pacific journal of information systems
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• v.25 no.1
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• pp.179-210
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• 2015

Despite the increasing adoption of gamification and its huge potential in tourism, research in gamification is still limited. As preliminary findings show that the effectiveness of gamification depends on the context of its application and the players' use of the gamified app, this paper fills in these gaps: by exploring and analysing the application of gamification in a specific e-commerce tourism context; and assessing the gamification's effectiveness by measuring the players' gamification usage and the latter's behavioural and psychological outcomes. The gamified TripAdvisor website and its Facebook enabled gamification app are used as the specific context of the study. Findings from a survey conducted on TripAdvisor users provide useful practical and theoretical implications to gamification designers and researchers alike on how game mechanics can be designed for enhancing the users' motivation, flow, task involvement and engagement with the 'play' tasks, and so, increasing the gamification's effectiveness.

• The Journal of Information Systems
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• v.25 no.4
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• pp.1-21
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• 2016

Purpose The study analyzed the factors affecting continuance use and self-disclosure in the SNS(social networking service) context based on a dual-factor model. As SNS users have concerned privacy for a long time, privacy concern affects continuous use and self-disclosure. In details, concern over privacy may have a stronger effect on self-disclosure than on continuance use as users' personal information can be more exposed during posting their dailies and photos. Design/Methodology/Approach SNS benefits, trust in SNS providers, and social influence are served as the key enablers and privacy concern as the inhibitor. Moreover, the relative impacts of SNS benefits and privacy concern on continuance use and self-disclosure were analysed in this study. From the data of 327 Facebook users, the researchers tested proposed theoretical model by using PLS. Findings Users' continuance intention and self-disclosure behavior are differently affected by different antecedents. Trust in SNS provider had a significant effect on self-disclosure intention, while it has no significant effect on continuance intention. Concern over privacy was negatively related to self-disclosure intention, while it was positively associated with continuance intention.