• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2012년도 추계학술대회
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• pp.903-905
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• 2012

최근 증강현실(Augmented Reality, AR)에 대한 연구가 활발히 진행 중이고, 소셜 네트워크 시스템(Social Network System)에 증강현실 기능의 추가 필요성이 부각되고 있다. 본 논문에서는 소셜 네트워크를 위한 GPS기반 증강현실 시스템을 제안한다. 제안한 시스템은 페이스북(facebook)에서 친구 목록을 자동으로 동기화하여 최근 체크인 좌표를 추가하고, AR을 이용하여 추가된 위치 좌표를 실제 환경에서 표현하는 시스템이다. 기존 이용자들이 사용했던 마커 기반 AR 시스템은 핸드 장치 구동에 필요한 프로세싱 빈도와 저장 공간의 소모가 많다. 위치 기반 AR 어플리케이션은 기존 마커기반 AR 시스템의 단점을 해결 할 수 있다. 따라서, 본 논문의 시스템은 향후 iOS 핸드 장치를 가지고 있는 사용자가 GPS기반 AR 시스템은 Wifi와 4G 네트워크에 대해 최적의 속도를 자동으로 검색하여 사용하여 소셜 네트워크 서비스의 제공이 가능하다.

• 농촌지도와개발
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• 제24권4호
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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.

• 지식경영연구
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• 제19권1호
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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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• 제8권11호
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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.

• 정보과학회 논문지
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• 제41권10호
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• pp.785-791
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• 2014

트위터는 페이스북과 더불어 전 세계적으로 인기 있는 SNS(Social Network Service)이다. 트위터에서 이메일 인증 방식을 악용하여 대량 생성된 스패머 계정은 유해한 콘텐츠로 트위터 사용자들에게 불편함을 준다. 본 논문에서는 이러한 문제를 해결하고자 관계 기반 특징을 이용한 스패머 탐지 기법을 제안한다. 관계 기반 특징이란 사용자의 호감 정도를 표현할 수 있는 친구 관계 특징과 사용자 간의 유사성을 나타낼 수 있는 유형 관계 특징들을 의미한다. 기존의 스패머 탐지 기법과 본 논문에서 제안하는 탐지 기법의 성능을 스패머의 비율을 3%에서 30%까지 변화시키면서 비교 실험한 결과, 본 논문에서 제안하는 기법이 Naive Bayesian Classifier와 Decision Tree 모두에서 더 우수한 성능을 보였다.

• 한국통신학회논문지
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• 제38B권5호
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• pp.385-393
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• 2013

지난 10여 년간, 정보기술 분야의 패러다임은 기계중심에서 인간중심으로, 기술기반에서 사용자가 쉽게 정보시스템에 참여하고 활용 할 수 있는 사용자 기반으로 변화되었다. 즉 소셜 네트워크를 이용하여 정보를 상호 공유하는 소셜 검색의 형태로 변화하고 있으며, 이와 같이 사람과 사람을 연결 해 주는 소셜 네트워크 서비스는 웹서비스와 융합을 통해 친구 맺기, 친구 찾기, 유사한 관심사를 갖고 있는 사람들과의 정보공유, 선호도 검색, 정보 추천시스템 등 다양한 분야에 활용되고 있다. 본 논문에서는 토픽 기반 소셜 관계 랭크(TS_SRR : Topic Sensitive_Social Relation Rank) 알고리즘을 제안한다. 제안 알고리즘은 소셜 네트워크 서비스를 웹 검색 엔진과 통합하는 것을 목적으로 하며, 소셜 관계 지수, 즉 Social Relation Rank와 검색 결과에 대한 선호도 사이의 상관관계를 분석하였다. 실험 과정에서 소셜 네트워크 안에 존재하는 일반적인 사람들은 정보 공유시 특정 분야에 대해 관심사가 유사할 경우 잘 모르는 타인들에 비해 친밀도가 높은 친구를 더 신뢰한다는 것을 확인 할 수 있었다. 따라서 제안 알고리즘은 소셜 검색의 신뢰성을 향상 시킬 수 있을 것으로 판단된다.

• 농촌계획
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• 제9권3호
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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.

• 디지털산업정보학회논문지
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• 제8권4호
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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.

• 정보보호학회논문지
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• 제24권2호
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• pp.373-384
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• 2014

소셜 네트워크 서비스는 인터넷상에서 다른 사람들과 친구 또는 사회적 관계를 맺을 수 있는 양방향 서비스로써 개방성을 바탕으로 인적 교류 네트워크의 중심이 되었다. 그러나 최근에는 개방성을 악용하여 신뢰할 수 없는 유언비어가 확산되고 개인 정보를 침해하는 다양한 공격으로 인해 여러 사용자들이 피해를 보는 사례가 발생하였다. 따라서 소셜 네트워크상에서의 정보는 신뢰할 수 있는 사람에게 전달하거나 혹은 제공 받을 수 있어야 한다. 최근의 신뢰도 연구에서는 사용자와 밀접한 한 홉 사이를 기반으로 한 신뢰도 평가방법들이 주로 제시되었다. 그러나 소셜 네트워크의 교류가 기존의 시공간성이 갖는 제약을 넘어서고 사용자도 큰 폭으로 늘어나면서 한 홉 사이뿐 아니라 여러 홉 사이에서의 교류 역시 최근에 많이 증가하고 있다. 이러한 흐름에 맞춰 본 논문에서는 전이성 및 결합성을 이용하여 원거리에서도 신뢰도 평가가 가능한 효과적인 사용자 신뢰도 평가 스킴을 제안한다.

• International Journal of Computer Science & Network Security
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• 제21권7호
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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.