• Knowledge Management Research
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• v.12 no.5
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• pp.25-40
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• 2011

Today, Internet users start off using heavily SNS(Social Network Site) such like, Facebook, Twitter. The reason of the growth of using SNS would be closely related to the various services of gaming, playing, entertainment items, sharing information etc., provided by the SNS, technically, the most important one out of the services provided would be behaving of sharing knowledge among people who connected and networked in the site. In sum, we assume that the users may communicate well each other and pay attention to build closely a social network using that kind of activities. However, nevertheless the new trends of communications and sharing knowledge become popular, researchers have just began the research issues in explaining why Internet user rush into SNS and enjoy the time in there. Therefore, we investigate on the reasons of posting knowledge voluntarily in the SNS and how others response to the posted information and actually affected by the behavior. We appled personal relation and social identity theory for this study, which personal relation in SNS may affect on social identity and make them produce knowledge generation. We found that social identity and involvement in SNS is closely related and influence knowledge creation and generation. This empirical study resulted in the importance of social relations in SNS, which leads to a sharing knowledge.

• Korean Journal of Human Ecology
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• v.22 no.2
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• pp.283-300
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• 2013

As one of the most popular forms of social commerce, on-line social commerce can provide many benefits for consumers, such as lower prices, information sharing, and so on. This research attempted to compare the differences of social commerce participation behavior between Korean consumers and Chinese consumers. The paper also studied the effect of demographic factors and individual propensities on consumer's participation behavior, such as the need for cognition, innovativeness, interactivity, reliability, groupism, and price consciousness. The results and conclusions of this research are as follows. First, consumer's individual propensities are different between China and Korea. In general, Korean participants have a higher level of innovativeness and price consciousness and a lower level of groupism than Chinese participants. Second, the influential factors of social commerce website visiting frequency and the participation in social commerce are different between the two countries. In Korea, consumer's age, innovativeness, and price consciousness have evident effects on the visiting frequency of social commerce websites. While in China, consumer's education, job, innovativeness, and groupism are significant.

• Knowledge Management Research
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• v.13 no.3
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• pp.1-16
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• 2012

Nowadays, many first-time Internet users start off heavily using SNSs (Social Network Sites), such as Cyworld, Facebook, and Twitter. The reason for the growth of SNS use is closely related to the various services of gaming, playing, using entertainment items, sharing knowledge etc., provided by the SNS; technically, the most important of the services provided would be the behavior of sharing knowledge among people connected and networked in the site. In sum, we assume that the users may communicate well with each other and pay attention to building a close social network using the abovementioned activities. However, researchers have just begun to focus on the issues explaining why Internet users rush into SNSs and enjoy their time there. Therefore, we investigated the reasons for posting and sharing knowledge voluntarily on the SNS and how others respond to the posted knowledge and are actually affected by the behavior. We applied social identity theory and social capital theory in this study to find which network externalities in SNSs may affect online identity-based attachment and cause them to produce a knowledge sharing generation. We found that people's online identity in SNSs is closely related to and influences knowledge sharing. This empirical study resulted in the importance of social relations in SNSs, which leads to sharing knowledge.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.602-604
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• 2011

Due to wide usage of smartphones and mobile internet, mobile devices are used in various fields such as sending SMS, participating SNS, retrieving information and the number of users taking advantage of them are growing. The keypads of a mobile device are relatively smaller than those of desktop computers. Thus, the user has a difficulty in input sentences quickly and correctly. In this study, we introduce some string recommendation and modification techniques which can be used for helping a user input in mobile devices quickly and correctly. We describe a TRIE dictionary and n-gram language model which are the main technologies of the keyword recommendation applied to the online search engines.

• Journal of Information Technology Applications and Management
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• v.20 no.2
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• pp.127-146
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• 2013

The online social networking services (SNS) have been growing as the means of communication. In this study, we investigated word-of-mouth (WOM) effect under the SNS environment and evaluated the impact of message sender's influence on the WOM effect. Especially, this study focused on the betweenness centrality calculated through the social network analysis (SNA) of SNS network information, and proposed it as the measure of WOM message sender's influence, SNA may provide more accurate and objective measures than subjective self-reporting survey method. Fifty-one Facebook users responded to each of their four Facebook friends, who had been selected based on their betweenness centrality, Statistical analyses were performed using the responses and the betweenness centralities of the Facebook friends. The results showed that the direction (positive vs, negative) of a WOM message in SNS had an impact on the attitude of the message receiver toward the product. Moreover, the betweenness centrality of the message sender as well as his/her opinion leadership had a moderating effect on the WOM effect. Opinion leadership is a measure that has been frequently used for indicating the influence of WOM message sender in the previous studies. Considering the result that the betweenness centrality of the message sender was Significantly correlated to his/her opinion leadership, the betweenness centrality can be used for indicating the influence of WOM message sender.

• Journal of Information Technology Applications and Management
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• v.20 no.2
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• pp.109-125
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• 2013

As the number of SNS users is increasing, it has been very important how companies use SNS strategically. As a result, studies have been performed for the utilization of SNS. Most of the studies, however, focused on the overall characteristics of SNS and did not consider the characteristics of individual SNS. This study classified the main purpose of SNS use as relation-oriented purpose and information-oriented purpose, and identified the types of SNS from two viewpoints : service type and openness. Based on the classification, this study identified the characteristics of Cyworld, Facebook, and Twitter respectively, and analyzed the difference of the purpose of SNS users according to the characteristics of each service. The results showed that more users had the information-oriented purpose in the order of Twitter, Facebook, and Cyworld. There was no difference in the relation-oriented purpose among the three services. The analyses of the motive to join a group or a party made similar results. The results of additional analyses showed that the ratio of users with many acquaintances was high in the order of Facebook, Twitter, and Cyworld. In addition, more users checked their timeline or news feed more frequently in the order of Facebook, Twitter, and Cyworld.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.113-122
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• 2011

Social Network Service(SNS) has become a hot trend as a web service which helps users construct social relationships in the web and enables online communication. The information about user activities and behaviors obtained from the SNSs is expected to be an useful knowledge source for other services such as recommendation services. Most of previous researches on SNS rely on analyzing overall network topology and surveying the activities in a one-dimensional aspect. This paper propose a system for measuring multi-dimensional interaction through the activities in a SNS. The proposed system delivers an unified profile (consisting of profile and multi-dimension interaction) model from user-activities in Twitter.com. At the experimental section, some meaningful perspectives on a set of the unified profiles are described.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.107-113
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• 2016

Following the recent advancement in the use of social networks, a vast amount of different online reviews is created. These variable online reviews which provide feedback data of contents' are being used as sources of valuable information to both contents' users and providers. With the increasing importance of online reviews, studies on opinion mining which analyzes online reviews to extract opinions or evaluations, attitudes and emotions of the writer have been on the increase. However, previous sentiment analysis techniques of opinion-mining focus only on the classification of reviews into positive or negative classes but does not include detailed information analysis of the user's satisfaction or sentiment grounds. Also, previous designs of the sentiment analysis technique only applied to one content domain that is, either product or movie, and could not be applied to other contents from a different domain. This paper suggests a sentiment analysis technique that can analyze detailed satisfaction of online reviews and extract detailed information of the satisfaction level. The proposed technique can analyze not only one domain of contents but also a variety of contents that are not from the same domain. In addition, we design a system based on Hadoop to process vast amounts of data quickly and efficiently. Through our proposed system, both users and contents' providers will be able to receive feedback information more clearly and in detail. Consequently, potential users who will use the content can make effective decisions and contents' providers can quickly apply the users' responses when developing marketing strategy as opposed to the old methods of using surveys. Moreover, the system is expected to be used practically in various fields that require user comments.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.427-430
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• 2014

최근 온라인상에 공개된 정보에서 개인정보 노출 여부를 분석하고 노출된 개인정보에 대한 위험도를 평가하는 기술이 연구되고 있다. 이와 같은 연구를 위해서는 다양한 경로에서 수집되는 개인정보들에 대한 사용자 ID 연결이 먼저 이루어져야 한다. 그래서 본 논문에서는 페이스북과 트위터 사용자를 연결할 수 있는 방안을 제시하고, 그 성능을 분석했다. 총 5가지 정보에 대한 유사도 측정 실험을 진행하여 각각에 정보가 페이스북과 트위터 사용자를 연결하는데 미치는 영향력을 확인했다. 정보의 영향력은 지역(72.2%), 링크(52%), 이름(51.3%), 이미지(11%), 관계(1%) 순으로 확인되었다.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.197-216
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• 2022

With the development of Internet and mobile technology and the spread of social media, a large amount of information is being generated and distributed online. Some of them are useful information for the public, but others are misleading information. The misleading information, so-called 'fake news', has been causing great harm to our society in recent years. Since the global spread of COVID-19 in 2020, much of fake news has been distributed online. Unlike other fake news, fake news related to COVID-19 can threaten people's health and even their lives. Therefore, intelligent technology that automatically detects and prevents fake news related to COVID-19 is a meaningful research topic to improve social health. Fake news related to COVID-19 has spread rapidly through social media, however, there have been few studies in Korea that proposed intelligent fake news detection using the information about how the fake news spreads through social media. Under this background, we propose a novel model that uses Graph2vec, one of the graph embedding methods, to effectively detect fake news related to COVID-19. The mainstream approaches of fake news detection have focused on news content, i.e., characteristics of the text, but the proposed model in this study can exploit information transmission relationships in social engagement networks when detecting fake news related to COVID-19. Experiments using a real-world data set have shown that our proposed model outperforms traditional models from the perspectives of prediction accuracy.