• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.903-905
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• 2012

Recent research on Augmented Reality is Actively expand and Augmented reality feature added to the social network system (Social Network System) has become a necessity. In this paper, GPS-based Augmented Reality System for Social Network is introduced, is proposed. This system can add recent check-in friends in facebook by automatically to synchronizing the location coordinate, and it could also adding location coordinates system is represented in a real-world environment by AR, is Marker-based AR system that was Commonly used AR system is a huge cost by handheld devices in processing and storage space, the disadvantages of the marker-based AR systems can be solved by using Location-based AR applications. Therefore, the proposed GPS-based Augmented Reality System for Social Network, automatically searches for the optimal speed for Wifi and 4G network to iOS Hand AR system was desired in future.

• Journal of Agricultural Extension & Community Development
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• v.24 no.4
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• pp.223-235
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• 2017

This study aims to identify the factors affecting the depression of elderly women in rural areas, by focusing on social network and sense of community. The questionnaires were conducted from July to September, 2016 by face-to-face interviews with the elderly women using the senior citizen center in rural areas. As a result, 302 questionnaires were collected, and of which 292 cases were utilized for the final analysis. The analysis revealed that socio-demographic characteristics, social network, and community consciousness had a significant effect on depression. The main results are summarized as follows. First, in first model, age, education, subjective health status, and subjective economic status were found to affect depression. Second, in second model, by adding the social network, the explanation power increased, and the social network of friends/neighbors were proven to be an influence on depression. Third, in third model, explanation power increased when sense of community was added, and it was proven that sense of community had an effect on depression. Finally, when the socio-demographic characteristics and the social network were controlled, the sense of community had more influence on the depression than the social network.

• Knowledge Management Research
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• v.19 no.1
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• pp.41-57
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• 2018

While there are lots of studies on examining the effects of social rapport in many research areas, however, there is a little work in examining the effect of the social rapport in social network service (SNS) contexts. Thus, this study attempts to examine the effect of social rapport in SNS settings. To address the research questions, this study has presented its hypotheses and conducted three experimental approaches by collecting 180 data from student subjects who have prior experiences on using SNSs to verify the hypotheses. This study has examined three experiments the effects of characteristics of Facebook(i.e. the number of mutual friends, the number of post likes, and the post personalities) on the social rapport and user responses. This study has conducted two-way ANOVA to verity its proposed research hypotheses. Based on three experiments, this study found that both the effects of the number of post likes and the number of post likes on the social rapport were not significant. Based upon empirical findings, this study has demonstrated how the effects of social rapports in SNSs were different from those of previous studies, and brought more attentions to the relevant literature.

• 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 KIISE
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• v.41 no.10
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• pp.785-791
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• 2014

Twitter is one of the most famous SNS(Social Network Service) in the world. Twitter spammer accounts that are created easily by E-mail authentication deliver harmful content to twitter users. This paper presents a spammer detection method that utilizes features based on the relationship between users in twitter. Relationship-based features include friends relationship that represents user preferences and type relationship that represents similarity between users. We compared the performance of the proposed method and conventional spammer detection method on a dataset with 3% to 30% spammer ratio, and the experimental results show that proposed method outperformed conventional method in Naive Bayesian Classification and Decision Tree Learning.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.5
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• pp.385-393
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• 2013

In the past decade, a paradigm shift from machine-centered to human-centered and from technology-driven to user-driven has been witnessed. Consequently, Social search is getting more social and Social Network Service (SNS) is a popular Web service to connect and/or find friends, and the tendency of users interests often affects his/her who have similar interests. If we can track users' preferences in certain boundaries in terms of Web search and/or knowledge sharing, we can find more relevant information for users. In this paper, we propose a novel Topic Sensitive_Social Relationship Rank (TS_SRR) algorithm. We propose enhanced Web searching idea by finding similar and credible users in a Social Network incorporating social information in Web search. The Social Relation Rank between users are Social Relation Value, that is, for a different topics, a different subset of the above attributes is used to measure the Social Relation Rank. We observe that a user has a certain common interest with his/her credible friends in a Social Network, then focus on the problem of identifying users who have similar interests and high credibility, and sharing their search experiences. Thus, the proposed algorithm can make social search improve one step forward.

• Journal of Korean Society of Rural Planning
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• v.9 no.3 s.20
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• pp.1-7
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• 2003

As the proportion of the elderly population in rural area is growing rapidly, the quality of life of the rural elderly is becoming a major concern. According to Rowe and Kahn(1997), active and productive engagement in society is a central component of successful aging. Yet, the effect of various social support network on psychological well-being of the rural elderly is not well known. This study is an attempt to empirically examine the connection between social support network and psychological well-being of the rural elderly. For this purpose, community welfare specialists gathered data from 1033 rural elderly in 32 villages, using structured questionnaires. The statistical methods used for the data analysis were descriptive statistics, cross tables, ANOVA and hierarchical regression analysis using spss wins 10.0 program. The major findings of this study are as follows: The majority of rural elderly have social support networks composed of more than one person and the mean number of their social support network was ten persons. The elderly who keep frequent contact with many adult children and friend/neighbor are happier than the elderly who keep contact with fewer number of children and friends. The size of the network of relatives significantly affects the level of loneliness of the elderly. Theoretical and practical implications of this study for the improvement of the quality of life of the rural elderly is discussed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.43-51
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• 2012

Web 3.0 is the next-generation of the World Wide Web and is included two main platforms, semantic technologies and social computing environment. The basic idea of web 3.0 is to define structure data and link them in order to more effective discovery, automation, integration, and reuse across various applications. The semantic technologies represent open standards that can be applied on the top of the web. The social computing environment allows human-machine co-operations and organizing a large number of the social web communities. In the recent years, recommender systems have been combined with ontologies to further improve the recommendation by adding semantics to the context on the web 3.0. In this paper, we study previous researches about recommendation method and propose a recommendation method based on web 3.0. Our method scores documents based on context tags and social network services. Our social scoring model is computed by both a tagging score of a document and a tagging score of a document that was tagged by a user's friends.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.2
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• pp.373-384
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• 2014

The social network service is the bidirectional media that many users can build relations not only friends but also other people. However, a process to approach in the social network is so simple that untrustable information, which malignant users make, is spreaded rapidly in many the social network uses. This causes many users to suffer material or psychological damages. Because of openness in the social network, there will be higher risk of the privacy invasion. Therefore, sensitive information should be transferred or provided only to reliable users. In general, because many users exchange among one hops, many researches have focused on one hop's trust evaluation. However, exchanges between users happen not only one joint bridege but also far nodes more than two nodes on account of dense network and openness. In this paper we propose the efficient scheme combining transitivity and composability for remote users.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.317-323
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• 2021

Social media is increasingly becoming a part of our daily life for communicating each other. There are various tools and applications for communication and therefore, identity theft is a common issue among users of such application. A new style of identity theft occurs when cybercriminals break into WhatsApp account, pretend as real friends and demand money or blackmail emotionally. In order to prevent from such issues, data mining can be used for text classification (TC) in analysis authorship attribution (AA) to recognize original sender of the message. Arabic is one of the most spoken languages around the world with different variants. In this research, we built a machine learning model for mining and analyzing the Arabic messages to identify the author of the messages in Saudi dialect. Many points would be addressed regarding authorship attribution mining and analysis: collect Arabic messages in the Saudi dialect, filtration of the messages' tokens. The classification would use a cross-validation technique and different machine-learning algorithms (Naïve Baye, Support Vector Machine). Results of average accuracy for Naïve Baye and Support Vector Machine have been presented and suggestions for future work have been presented.