• Journal of Internet Computing and Services
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• v.8 no.4
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• pp.137-147
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• 2007

As Web-based online communities are rapidly growing, the agents in social groups need to know their measurable belief of trust for safe andsuccessful interactions. In this paper, we propose a computational model of trust resulting from available feedbacks in online communities. The notion of trust can be defined as an aggregation of consensus given a set of past interactions. The averagetrust of an agent further represents the center of gravity of the distribution of its trustworthiness and untrustworthiness. And then, we precisely describe the relationship between reputation, trust, and averagetrust through a concrete example of their computations. We apply our trust model to online internet settings in order to show how trust mechanisms are involved in a rational decision-making of the agents.

• The Journal of Bigdata
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• v.4 no.1
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• pp.99-118
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• 2019

This study used network analysis and clustering techniques to analyze studies on social media participation. As a result of the main path analysis, 37 major studies were extracted and divided into two networks: community-related networks and new media-related. Network analysis and clustering result in four clusters. This study has the academic significance of using academic data to grasp research trends at a macro level and using network analysis and machine learning as a methodology.

• International Journal of Advanced Culture Technology
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• v.6 no.2
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• pp.58-64
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• 2018

This main purpose of the study is to identify social network of communicators sharing information on Bokjiro for publicizing welfare policy. This study employs NodeXL pro to understand networks and their role in the social network. The data for social network analysis was collected from Twitter for a week. The result of the analysis shows that the social network of communicators on Bokjiro does not have many nodes. It also has an independent network with high possibility of information distortion. Little communicators have controlling power in information flow in one way of communication. According to the result, it is not effective for marketing strategy of welfare policy in providing online information through Bokjiro. The study suggests that the government should use the transactional approach to marketing based on agent-oriented activity focusing on the exchange relationship between information providers and demanders in an age of networked intelligence.

• International Journal of Contents
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• v.15 no.2
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• pp.29-37
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• 2019

This study investigates how adolescents' smartphone attachment, social anxiety, and offline and smartphone network sizes are related to their friendship in regards to maintaining either a strong or weak bond. Based on an online survey involving 402 adolescent smartphone users in South Korea, this study found that smartphone attachment was positively related to a strong ties friendship maintenance and negatively related to weak ties friendships. Similarly, social anxiety was found to be negatively associated with friendship maintenance for both strong and weak - tie relationships. More importantly, this study revealed that the types and size of social networks moderated the relationships among adolescents with smartphone attachment, social anxiety, and friendship maintenance through smartphones.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.89-105
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• 2017

As the advances of technology in mobile networking and the popularity of online social networks (OSNs), the mobile social networks (MSNs) provide opportunities for marketing strategy. Therefore, understanding the information diffusion in the emerging MSNs is a critical issue. The information diffusion address a problem of how to find the proper initial nodes who can effectively propagate as widely as possible in the minimum amount of time. We propose a new diffusion scheme, called Hotspot DBC, which is to find k influential nodes considering each node's mobility behavior in the hotspot zones. Our experiments were conducted in the Opportunistic Network Environment (ONE) using real GPS trace, to show that the proposed scheme results. In addition, we demonstrate that our proposed scheme outperforms other existing algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.5
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• pp.257-266
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• 2017

Two remarkable problems of recent online social network are information overflow and information overload. Since the mid-1990s, many researches to overcome these issues have been conducted with information recommender systems and context awareness based personalization techniques, the importance of trust or relationship between users to discover influential information has been increasing as recent online social networks become huge. But almost researches have not regarded trust or relationship in real world while reflecting them in online world. In this paper, we present a novel method how to discover influential and spreadable information that is highly personalized to a user. This valuable information is extracted from an information set that consists of lots of information user missed in the past, and we assumes important information is likely to exist in this set.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1020-1033
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• 2021

Nowadays, online or mobile social network services (SNS) are very popular and widely spread in our society and daily lives to instantly share, disseminate, and search information. In particular, SNS such as YouTube, Flickr, Facebook, and Amazon allow users to upload billions of images or videos and also provide a number of multimedia information to users. Information retrieval in multimedia-rich SNS is very useful but challenging task. Content-based media retrieval (CBMR) is the process of obtaining the relevant image or video objects for a given query from a collection of information sources. However, CBMR suffers from the dimensionality curse due to inherent high dimensionality features of media data. This paper investigates the effectiveness of the kernel trick in CBMR, specifically, the kernel principal component analysis (KPCA) for dimensionality reduction. KPCA is a nonlinear extension of linear principal component analysis (LPCA) to discovering nonlinear embeddings using the kernel trick. The fundamental idea of KPCA is mapping the input data into a highdimensional feature space through a nonlinear kernel function and then computing the principal components on that mapped space. This paper investigates the potential of KPCA in CBMR for feature extraction or dimensionality reduction. Using the Gaussian kernel in our experiments, we compute the principal components of an image dataset in the transformed space and then we use them as new feature dimensions for the image dataset. Moreover, KPCA can be applied to other many domains including CBMR, where LPCA has been used to extract features and where the nonlinear extension would be effective. Our results from extensive experiments demonstrate that the potential of KPCA is very encouraging compared with LPCA in CBMR.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.957-959
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• 2013

A SNS(Social Networking Service) is an online platform to build social networks or social relations among people who, for example, share free communication, information, and make more personal connections. In this paper, we find representative entities, develop relationships among them, and draw an ERD based on the entities and their relationships. And then we design a SNS database schema by converting the ERD into collections according to data model of MongoDB, which is an NoSQL database.

• International Journal of Contents
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• v.18 no.3
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• pp.21-33
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• 2022

Previous research has provided inconsistent findings as to whether socially (in)competent individuals benefit from social networking sites (SNSs) use. Based on the rich-get-richer model, some studies have shown that socially competent individuals expand their existing networks even further via SNSs use. Based on the poor-get-richer model, other studies have shown that those with poor social skills can achieve beneficiary outcomes from SNSs use by overcoming their deficient social resources of offline environments. The present study is devised to add evidence regarding how and why social skills are related to SNSs use. To this end, we tested the relationships between social competence and three types of Facebook communication activities: interaction, self-presentation, and passive observation. Further, drawing on the social cognitive theory, the mediating role of outcome expectancy in the relationship between social competence and Facebook communication activities was examined. Using an online survey in South Korea (N = 708), it was found that individuals with higher social competence were more likely than those with lower social competence to engage in interaction, self-presentation, passive observation on Facebook. Moreover, these relationships were mediated by outcome expectancy that the desired social outcomes could be achieved as a result of Facebook use.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.875-876
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• 2011

본 논문은 온라인 사회 연결망을 위한 개인정보 보호 방안들에 대해 알아보고, 각 방안이 사회 연결망의 특성 변화에 미친 영향을 분석한다. 분석 결과, 개인정보 보호 방안들은 사회 연결망의 특성을 크게 훼손시키는 것으로 나타났다