• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.7-17
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• 2017

Despite various types of online social networks having different topological and functional characteristics, the kinds of online social networks considered in social recommendations are highly restricted. The pervasiveness of social networks has brought scholarly attention to expanding the scope of social recommendations into more diverse and less explored types of online social networks. As a preliminary attempt, this study examined the information-sharing patterns of a new type of online social network - unilateral (directed) network - and assessed the feasibility of the network as a useful information source. Specifically, this study mainly focused on the presence of shared interests in unilateral networks, because the shared information is the inevitable condition for utilizing the networks as a feasible source of personalized recommendations. As the results, we discovered that user pairs with direct and distant links shared significantly more similar information than the other non-connected pairs. Individual users' social properties were also significantly correlated with the degree of their information similarity with social connections. We also found the substitutability of online social networks for the top cohorts anonymously chosen by the collaborative filtering algorithm.

• Journal of Information Technology Services
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• v.13 no.2
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• pp.173-184
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• 2014

As social network services has become one of the most successful web-based business, recommendation in social network sites that assist people to choose various products and services is also widely adopted. Collaborative Filtering is one of the most widely adopted recommendation approaches, but recommendation technique that use explicit or implicit social network information from social networks has become proposed in recent research works. In this paper, we reviewed and compared research works about recommendation using social network analysis and collaborative filtering in social network sites. As the results of the analysis, we suggested the trends and implications for future research of recommendation in SNSs. It is expected that graph-based analysis on the semantic social network and systematic comparative analysis on the performances of social filtering and collaborative filtering are required.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.6
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• pp.657-664
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• 2014

This study is targeted at users of social networks to investigate motives, motives based on information exchange, network density, and reliability of information, recognizing network. Result motivation is a social network analysis of information-seeking motivation, social influence motivation, entertainment motivation, motivation network formation, respectively. Network density is also information seeking motivations, social influence motivation, entertainment showed differences in motivation, information about the reliability of the difference between the difference was in all the motivational factors.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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• pp.47-57
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• 2015

Recently, Internet of Things (IoT) have become popular for research and development in many areas. IoT makes a new intelligent network between things, between things and persons, and between persons themselves. Social network service technology is in its infancy, but, it has many benefits. Adjacent users in a social network tend to trust each other more than random pairs of users in the network. In this paper, we propose recommendation technique using social network in Internet of Things environment. We study previous researches about information recommendation, IoT, and social IoT. We proposed SIoT_P(Social IoT Prediction) using social relationships and item-based collaborative filtering. Also, we proposed SR(Social Relationship) using four social relationships (Ownership Object Relationship, Co-Location Object Relationship, Social Object Relationship, Parental Object Relationship). We describe a recommendation scenario using our proposed method.

• Journal of Korean Library and Information Science Society
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• v.39 no.2
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• pp.169-186
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• 2008

Social Network has been known as friendship basis human relation service in online network. But a broad sense of Social Network can be explained as a mechanism which makes web evolve to information-ecosystem by human relation and network data which has been generated by the mass of people's cooperation and interchange. Social Network has been expanding their domain from friendship basis relation service to broad social relationship focus of matter of concern. It has been applied to diverse domain. Library community begins to take an interest in Social Network concept to apply user's interchange for information. This paper considers the concept of Social network and it's appliance to a library service. For the more, suggest basic element for vitalizing library user's Social network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3984-3996
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• 2014

Mobile social network can be seen as a specific application of the DTN (Delay Tolerant Network), in which the information propagation can be impacted by many social behaviors of the nodes. For a specific node, its social behaviors are various. For example, the node may not be interested in the information before receiving it and may also discard the information after getting it. On the other hand, people are more willing to forward the message to his friends. These interactive behaviors between nodes can be seen as social behaviors. It is easy to see that the impact of the social behaviors is related to the social ties, which can be manifested by the structure of the social network. State of the art works often simply assumes that the social networks can be divided into some communities. At present, some works find that the structure of some social networks is scale-free. To overcome this problem, this paper proposes a theoretical model to evaluate the impact of above social behaviors in the DTN-like scale-free network. Simulation shows the accuracy of the model. Numerical results show that both social behaviors and scale-free character have significant impact on information propagation. Moreover, the impact of social behaviors is related to the scale-free character of the networks.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.1-21
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• 2015

This paper aims to assess the feasibility of a new and less-focused type of online sociability (the watching network) as a useful information source for personalized recommendations. In this paper, we recommend scientific articles of interests by using the shared interests between target users and their watching connections. Our recommendations are based on one typical social bookmarking system, CiteULike. The watching network-based recommendations, which use a much smaller size of user data, produces suggestions that are as good as the conventional Collaborative Filtering technique. The results demonstrate that the watching network is a useful information source and a feasible foundation for information personalization. Furthermore, the watching network is substitutable for anonymous peers of the Collaborative Filtering recommendations. This study shows the expandability of social network-based recommendations to the new type of online social networks.

• Journal of Communications and Networks
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• v.17 no.2
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• pp.100-109
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• 2015

Mobile phone carriers face challenges from three synergistic dimensions: Wireless, social, and mobile. Despite significant advances that have been made about social networks and human mobility, respectively, our knowledge about the interplay between two layers remains largely limited, partly due to the difficulty in obtaining large-scale datasets that could offer at the same time social and mobile information across a substantial population over an extended period of time. In this paper, we take advantage of a massive, longitudinal mobile phone dataset that consists of human mobility and social network information simultaneously, allowing us to explore the impact of human mobility patterns on the underlying social network. We find that human mobility plays an important role in shaping both local and global structural properties of social network. In contrast to the lack of scale in social networks and human movements, we discovered a characteristic distance in physical space between 10 and 20 km that impacts both local clustering and modular structure in social network. We also find a surprising distinction in trajectory overlap that segments social ties into two categories. Our results are of fundamental relevance to quantitative studies of human behavior, and could serve as the basis of anchoring potential theoretical models of human behavior and building and developing new applications using social and mobile technologies.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.325-330
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• 2011

Due to the wide growth and popularity of social network website, large numbers of users discover these social network sites are a place where they can be able to spend their leisure time sharing interests, sharing ideas freely, sharing personal experience, and also to search for new friends or partners. These websites give an opportunity for its users to socialize with new people and to keep in touch or reconnect with current or old friends and families across disperse continents, which traditionally replace the common traditional methods. These social network websites need accurate and careful investigations and findings on the usability issues for effective interactivity and more usability. However, little research might have previously invested on the usability of these social network websites. Therefore, we propose a new framework to study and test the usability of these social network sites. We namely call our framework "Interactivity". This framework will enable developers to assess the usability of the social network sites. It will provide an overview of the user's behavior while interacting in these social network websites. Performance of the framework will be performed using Camtasia software. This software will entirely capture the interactivity of users including the screen and the movements, which the screen and the motion of the user action will undergo to analysis at the end of our research.

• Asia pacific journal of information systems
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• v.32 no.1
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• pp.168-190
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• 2022

This review aims to synthesize social network theories by drawing on the importance of social network perspectives in understanding knowledge management with technology in organizations. I provide an overview of prior social network research with the following core ideas: the primacy of relations between organizational actors, the utility of actors' embeddedness in social fields, the social utility of network connections, and the structural patterning of social life. On top of that, I summarize critical social perspectives (the social capital theory, the structural hole theory, the embeddedness perspective, the social exchange theory, the organizational learning theory, and the innovation diffusion theory) to suggest potential research questions for future studies in social network research in the knowledge management discipline.