• Journal of Information Technology Applications and Management
• /
• 제18권4호
• /
• pp.41-53
• /
• 2011

Trust prediction between users in social network based on the trust propagation assumes properties of transitivity and composability of trust propagation. But it has been hard to find studies which test on how those properties have been operated in real social network. This study aims to validate if the longer the distance of trust paths and the less the numbers of trust paths, the higher prediction error occurs using two real social network data set. As a result, the longer the distance of trust paths, we can find higher prediction error when predicting level of trust between source and target users. But we can not find decreasing trend of prediction error though the possible number of trust paths between source and target users increases.

• 가정과삶의질연구
• /
• 제20권4호
• /
• pp.149-164
• /
• 2002

The purpose of this study was to identify the types of social networks of urban housewives according to different network composition patterns and to analyze the structural and functional characteristics of identified types. The data used in this study were collected from 589 full-time housewives residing in Taejeon city. The major findings are as follows: 1) The social networks of housewives in urban nuclear families were classified into eight types: the kin network, the non-kin network, the kin-centered network, the friend-centered network, the neighbor-centered network, the associate-centered network, the parallel network, and the decentralized network. 2) The structual characteristics (size, density, homogeneity, duration, proximity, frequency, closeness, direction) varied according to the type. The kin network type and the non-kin network type showed extreme degrees in network characteristics. The parallel network type and the decentralized network type showed an average level of network characteristics. The kin-, friend-, neighbor-, and the associate-centered types showed network characteristics of an intermediate level between the single-category types and the decentralized type. 3) The average levels of function of social network types were different in only two(service support, interference) of the six function areas(emotional support, service support, material support, information support, social companionship support, interference). The average level of service support by the non-kin network type was higher than other types. The average level of interference by the kin-centered network type was higher than other types, and that of the neighbor-centered network type was lower than other types. On the other hand, the total amount of function performance of social network types was different in all function areas. The total amount of social support given by the decentralized network type was greater than the other types. The total amount of interference given by the non-kin network type was smaller than the other types.

• 정보보호학회논문지
• /
• 제22권3호
• /
• pp.447-461
• /
• 2012

소셜 네트워크 서비스는 실시간 정보 공유의 새로운 매개체로 각광을 받고 있다. 하지만 소셜 네트워크를 통해 공유되는 정보는 사용자의 신분이나 생활 패턴 등을 노출시킬 수 있는 민감한 정보가 포함되어 있기 때문에 사용자의 프라이버시 침해가 빈번히 발생한다. 이러한 문제를 해결하기 위해 소셜 네트워크 환경에서 프라이버시를 보호하는 데이터 공유 기법에 대한 연구가 활발히 진행되고 있다. 본 논문에서는 소셜 네트워크에 적합한 프라이버시 보존 데이터 공유 기법을 제안한다. 제안하는 기법은 암호화된 데이터에서 검색자가 선택한 키워드가 모두 포함되어 있는 데이터를 검색할 수 있으며, 스토리지 서버에 대한 접근 권한을 부여받은 사용자는 누구나 데이터를 저장하고 검색할 수 있다. 또한 동적 환경인 소셜 네트워크의 특징에 적합하도록 효율적인 가입/탈퇴 기능을 제공한다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권3호
• /
• pp.1168-1188
• /
• 2018

Social Network Aggregators are used to maintain and manage manifold accounts over multiple online social networks. Displaying the Activity feed for each social network on a common dashboard has been the status quo of social aggregators for long, however retrieving the desired data from various social networks is a major concern. A user inputs the query desiring the specific outcome from the social networks. Since the intention of the query is solely known by user, therefore the output of the query may not be as per user's expectation unless the system considers 'user-centric' factors. Moreover, the quality of solution depends on these user-centric factors, the user inclination and the nature of the network as well. Thus, there is a need for a system that understands the user's intent serving structured objects. Further, choosing the best execution and optimal ranking functions is also a high priority concern. The current work finds motivation from the above requirements and thus proposes the design of a query processing system to retrieve information from social network that extracts user's intent from various social networks. For further improvements in the research the machine learning techniques are incorporated such as Latent Dirichlet Algorithm (LDA) and Ranking Algorithm to improve the query results and fetch the information using data mining techniques.The proposed framework uniquely contributes a user-centric query retrieval model based on natural language and it is worth mentioning that the proposed framework is efficient when compared on temporal metrics. The proposed Query Processing System to Retrieve Information from Social Network (QPSSN) will increase the discoverability of the user, helps the businesses to collaboratively execute promotions, determine new networks and people. It is an innovative approach to investigate the new aspects of social network. The proposed model offers a significant breakthrough scoring up to precision and recall respectively.

• 지능정보연구
• /
• 제17권2호
• /
• pp.39-60
• /
• 2011

웹 2.0 기술이 소개된 이후 소셜 네트워크 서비스는 미래 정보기술의 기초로서 중요하게 인식되고 있다. 이에, 웹2.0 환경에서 소셜 네트워크를 구축하기 위하여 온톨로지 기반의 사용자 프로필 기술 도구인 FOAF를 활용하기 위한 다양한 연구가 이뤄지고 있다. 그러나 FOAF를 이용하여 소셜 네트워크를 생성 및 관리하는 대부분의 방법은 시간의 흐름에 따라 변화하는 사용자의 소셜 네트워크를 자동적으로 반영하기 어려운 단점이 있으며 다양한 소셜 미디어 서비스가 제공되는 환경에서는 FOAF를 동적으로 관리하기가 쉽지 않다. 따라서 본 논문에서는 기존 FOAF를 이용한 소셜 네트워크 추출방법의 한계를 극복하기 위하여 사용자 프로파일 기술 언어인 FOAF와 웹 저작물 출판 매커니즘인 RSS를 OLAP 시스템에 적용시켜 동적으로 FOAF를 갱신하고 관리하기 위한 방법을 제안한다. 본 논문에서 제안하는 방법은 수집한 FOAF와 RSS 파일들을 스타스키마로 설계된 데이터베이스에 넣어 OLAP 큐브를 생성한다. 그리고 OLAP 연산을 이용하여 사용자의 연결관계를 분석하고 FOAF에 그 결과를 반영한다. 본 논문에서 제안하는 방법은 이기종 분산처리 환경 하에서 데이터의 상호호환성을 보장할 뿐만 아니라 시간의 흐름에 따른 사용자의 관심 및 이슈 등의 변화를 효과적으로 반영한다.

• 가정과삶의질연구
• /
• 제14권3호
• /
• pp.151-166
• /
• 1996

This study examined the effects of social support on the perceived life satisfaction of middle-aged wives. To better understand the effects of social support on the perceived life satisfaction of middle-aged wives this study considered the following four different types of social support: emotional material informational and companionshp support. In addition each type of social support from the following five sources-the family of origin network the family of husband network friends neighbors and social organization-were examined separately in relation to the perceived life satisfaction of middle-aged wives. The data for his study were collected in the winter of 1995 from 417 housewives in Pusam wholse youngest child has graduated from elementary schools. Analyses of these data proved that (1) contrary to the classical "middle-age cristis" theory the average level of the perceived life satisfaction of middle-aged wives is relatively high; (2) there is a strong positive correla ion between the global level of social support and the overall life satisfaction of middle-aged wives; (3) the family of origin network is the most important provider of social support to middle-aged wives; and (4) the effects of social support on the perceived life satisfaction of middle-aged wives differ across types and sources of support. Findings showed that emotional informational and companionship support from the family of origin network have significantly positive effects on the perceived life satisfaction of middle-aged wives. On he other hand the material support from the family of origin network proved to have little effect.le effect.

• 한국콘텐츠학회논문지
• /
• 제20권2호
• /
• pp.96-104
• /
• 2020

온라인 쇼핑몰의 활성화로 소비자들의 소비 활동이 활발해짐에 따라 기업들은 매출 증대를 위해 소비자의 상품 트렌드 분석을 수행하고 있다. 기존의 상품 트렌드 분석 기법들은 온라인 쇼핑몰 사용자의 활동만을 고려하여 분석하기 때문에 구매 이력이 없거나 새로운 상품에 대한 트렌드를 파악하기 어렵다. 본 논문에서는 쇼핑몰에서 사용자의 트렌드와 잠재적 고객의 트렌드를 분석하기 위해 온라인 쇼핑몰 데이터와 소셜 네트워크 데이터를 결합한 트렌드 분석 기법을 제안한다. 제안하는 기법은 서비스 내 데이터 분석을 위해 사용자의 활동로그를 분석하고 활동 로그가 없는 잠재적인 사용자들의 관심도를 반영하기 위해 소셜 네트워크 데이터에서 단어 집합 추출을 통해 생성한 핫 토픽을 결합하였다. 최종적으로 상품 지수와 소셜 네트워크에서의 언급수를 활용하여 시간에 따른 상품 트렌드 변화를 탐지한다. 소셜 네트워크 데이터를 활용한 성능 평가를 통해 제안하는 기법의 우수성을 입증한다.

• 여성건강간호학회지
• /
• 제9권1호
• /
• pp.50-60
• /
• 2003

Purpose : The purpose of this study was to evaluate the factors which are related to the maternal role performance of first-time mother to improve the health of infant. Specifically a basic hypothetical model was developed based on the previous study about a model of social networks. Method : The survey was done from January to February in 2001. Total 257 mothers who have four to twelve month old first-time baby was interviewed in five community health center around country(Seoul, Choung-ju, Asan, Cheon-an, Jeju). Finally 247 data was analyzed. Data analysis was done with LISREL 8.20 program for covariance structural analysis. Results : Compared to the hypothetical model, the revised model has become parsimonious and had a better fit to the data ($X^2=167.55$ (p값=.00), $x^2/df=1.48$, GFI=0.97, AGFI=0.95, RMR=0.049, NFI=0.98, NNFI=0.99, CN=222.53). All predictive variables of the maternal role of first-time mother explained 30% of total variance in model. Social network structural characteristics and social network interactional characteristics had significant effect on the emotional support and the information support. And social network interactional characteristics had significant effect on the service support, material support and social companionship support. The service support and social companion ship support had significant effect on the maternal role strain. The emotional support and the social companion ship support had significant effect on the maternal role of first-time mother. Conclusion : As the conclusion of this study, there is in need of the developing the programmes focussed on the social network for the first-time mother.

• 스마트미디어저널
• /
• 제6권3호
• /
• pp.41-48
• /
• 2017

Event detection using social media has been widespread since social network services have been an active communication channel for connecting with others, diffusing news message. Especially, the real-time characteristic of social media has created the opportunity for supporting for real-time applications/systems. Social network such as Twitter is the potential data source to explore useful information by mining messages posted by the user community. This paper proposed a novel system for temporal event detection by analyzing social data. As a result, this information can be used by first responders, decision makers, or news agents to gain insight of the situation. The proposed approach takes advantages of deep learning methods that play core techniques on the main tasks including informative data identifying from a noisy environment and temporal event detection. The former is the responsibility of Convolutional Neural Network model trained from labeled Twitter data. The latter is for event detection supported by Recurrent Neural Network module. We demonstrated our approach and experimental results on the case study of earthquake situations. Our system is more adaptive than other systems used traditional methods since deep learning enables to extract the features of data without spending lots of time constructing feature by hand. This benefit makes our approach adaptive to extend to a new context of practice. Moreover, the proposed system promised to respond to acceptable delay within several minutes that will helpful mean for supporting news channel agents or belief plan in case of disaster events.

• 가정과삶의질연구
• /
• 제27권5호
• /
• pp.91-99
• /
• 2009

This study investigates the relationships among emotional support from social network, ego-resiliency, and role conflict of teachers in kindergartens and day care centers. The subjects were 192 teachers who worked in kindergartens or child care centers in Daegu and Gyeongbuk Province. Questionnaires, which require self-report by teachers, were used to investigate the emotional support from social network, ego-resiliency, and role conflict. The collected data were analyzed by Pearson's correlation, single and multiple regressions, using SPSS Win 15.0. The results are as follows. (1) Emotional support from social network and ego-resiliency was negatively associated with the role conflict of teachers in kindergartens and day care centers. (2) Emotional support from social network was positively associated with ego-resiliency. (3) Emotional support from social network partly exerted indirect effects on role conflict mediated by ego-resiliency. But direct effect of emotional support from social network on role conflict was more than the indirect effect. These results indicate that a higher level of emotional support from social network is more likely to lower role conflict of teachers.