• 경영정보학연구
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• 제13권3호
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• pp.141-163
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• 2011

인터넷을 중심으로 한 정보기술의 급격한 발전은 정보화 사회로의 패러다임 전환을 가져오면서 사회적 여론을 형성하는 과정에도 영향을 미치고 있다. 이에 따라 디지털 매체를 활용하여 온라인에서 정보를 생성하고 유통하며 사회적 합의에 이르는 정보처리 매커니즘의 변화에 대한 연구의 중요성이 증가하고 있다. 본 연구에서는 사회적 정보처리 과정의 고찰을 통하여 사회적 합의도출 및 제도화의 프로세스 모델을 도출하고 인터넷 매체에서의 정보처리 특성을 분석하였다. 정보처리 매커니즘의 변화를 분석하기 위하여 사회적 맥락 속에서 집단적 행동을 분석하는 질적 연구방법인 인류학적 접근법(ethnographic approach)을 적용하여 2가지 사례를 관찰 분석하였다. 사회적 컨센서스 형성과정은 사회적 의제의 제기, 여론 활동에서의 선택적 반영, 의제의 수용과 확산, 공론화와 사회적 합의, 제도화와 피드백이라는 5가지 단계로 구성되어진다. 인터넷 매체에서의 정보처리 특성은 사건에의 능동적 반응, 오피니언 리더의 역할 전이, 발의와 분석의 탄력성, 높은 확장성, 합의도출에의 적합성, 제도화와 상호작용 등 6가지로 제시하였다. 본 연구에서는 사회구성원의 정보를 공유하고 사회적 여론을 이끄는 과정을 설명하는 모텔을 제시함으로써 정보처리 구조를 사회적 네트워크 관점에서 고찰할 수 있는 이론적 기반을 마련하였다. 또한 그리고 인터넷 매체의 사회적 효용을 사회적 정보처리라는 새로운 기준으로 분석하여 정치, 커뮤니케이션 경영분야에서의 미디어 활용 및 의사결정의 합리성 제고에 기여할 것으로 보인다.

• 대한가정학회지
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• 제38권1호
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• pp.9-23
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• 2000

This study was designed to test the differences in children's social information-processing patterns and bahavioral characteristics among four different groups of peer status, and to evaluate the predictability of peer status from social information-processing and social behavior. In addition, age and sex differences were assessed. The subjects were 80 boys and 80 girls identified as popular, average, neglected, and rejected by their peers in the first and the third grade. They responded to a sociometric test and three hypothetical social dilemmas, while behavioral characteristics were rated by their teachers. The data were analyzed by ANOVAs, and discriminant analyses. The results showed that children's social information-processing patterns were not significantly different by peer status except the number of interventions requested. Whereas children's behavioral characteristics were different by peer status in all of the four domains. Children's social information-processing patterns and behavioral characteristics were different in part by age and sex. The important predictors of peer status were hyperactive-distractive, anxious-withdrawn, sociable-prosocial behaviors, and the number of interventions requested.

• 대한가정학회지
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• 제47권1호
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• pp.105-113
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• 2009

The purpose of this study was to explore differences in social information processing according to children's sex and types of aggression in response to instrumental and relational provocation factors. Two hundred and fifty-one 4, 5, and 6 graders were selected from an elementary school in Seoul. To evaluate their social information processing, the Intent Attributions and Feelings of Distress(Crick, 1995; Fitzgerald & Asher, 1987) and Response Decision Instrument(Crick & Werner, 1998) were revised and analyzed. A peer-nomination measure(Crick, 1995; Crick & Grotpeter, 1995) was used to select aggressive groups. Data were subjected to descriptive statistical analysis and multivariate [2(sex: M, F)${\times}$3(type of aggression: overt, relational, overt and relational aggression)] analysis of variance. Findings revealed that children's social information processing patterns were different according to sex and type of aggression. Also aggressive children responded differently in their social information processing according to instrumental and relational provocation factors. Implications of these findings for the role of gender, aggression type, and provocation type are discussed in order to better understanding of children's social information processing.

• 디지털산업정보학회논문지
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• 제10권1호
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• pp.61-71
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• 2014

Social networking services have changed the way people communicate. Rapid growth of information generated by social networking services requires effective search methods to give useful results. Over the last decade, social search methods have rapidly evolved. Traditional techniques become unqualified because they ignore social relation data. Existing social recommendation approaches consider social network structure, but social context has not been fully considered. Especially, the friend recommendation is an important feature of SNSs. People tend to trust the opinions of friends they know rather than the opinions of strangers. In this paper, we propose a levelized data processing method for social search in ubiquitous environment. We study previous researches about social search methods in ubiquitous environment. Our method is a new paradigm of levelelized data processing method which can utilize information in social networks, using location and friendship weight. Several experiments are performed and the results verify that the proposed method's performance is better than other existing method.

• 아동학회지
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• 제27권3호
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• pp.149-168
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• 2006

This study examined the effects of maternal parenting behaviors, children's social information processing, daily hassles, and emotional regulation on school-age children's aggressive behaviors using Structural Equation Modeling(SEM) analysis. Subjects were 589 children in 4, 5, 6th grade and their mothers from three elementary schools in Seoul, Korea. Data were analyzed with descriptive statistics and SEM analysis by SPSS 12.0 and AMOS 4.0. The SEM shows differences between overtly aggressive and relationally aggressive children. Maternal parenting behaviors affected their children's overt aggression through children's emotional regulation. Additionally, maternal parenting behaviors affected children's overt aggression through children's daily hassles and social information processing. Maternal parenting behaviors influenced children's relational aggression through children's daily hassles and children's social information processing.

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

• Journal of Information Processing Systems
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• 제14권4호
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• pp.904-915
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• 2018

We demonstrate how social media content can be used to predict the unemployment rate, a real-world indicator. We present a novel method for predicting the unemployment rate using social media analysis based on natural language processing and statistical modeling. The system collects social media contents including news articles, blogs, and tweets written in Korean, and then extracts data for modeling using part-of-speech tagging and sentiment analysis techniques. The autoregressive integrated moving average with exogenous variables (ARIMAX) and autoregressive with exogenous variables (ARX) models for unemployment rate prediction are fit using the analyzed data. The proposed method quantifies the social moods expressed in social media contents, whereas the existing methods simply present social tendencies. Our model derived a 27.9% improvement in error reduction compared to a Google Index-based model in the mean absolute percentage error metric.

• International Journal of Advanced Culture Technology
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• 제7권1호
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• pp.96-102
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• 2019

The purpose of this study was to examine the effects of applying a program to enhance social information processing ability in schizophrenic patients. We confirmed the positive effects of the program on the theories of mind and attribution style, which are the social information elements of patients, and confirmed the effect of decreasing paranoid ideation. We used the theory of mind(hinting task, the false belief task), the attributional style questionnaire(external bias, personal bias), and the paranoia scale to test the effectiveness of the program. Specifically, in theory of mind, hinting task performance was improved(t=4.14, p=.000),. The scores of personal bias(t=-7.9, p=.000) and paranoid ideation(t=-2.98, p=.004) decreased. Further research is needed to verify the effectiveness of meta - cognitive training to enhance social information processing.

• 한국IT서비스학회지
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• 제11권2호
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• pp.319-337
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• 2012

To stress the importance of privacy in social networking, I presented an analysis on how information control and information management vulnerability influence trust and privacy concerns in social networking, and how trust and privacy concerns influence the sustainable usage intention of social network services. I also analyzed the factors affecting privacy concerns to present the method to alleviate social network users' concerns about privacy. Information collection control, information processing control and information management vulnerability were chosen and analyzed as the factors affecting privacy concerns. The results showed that information collection control and information management vulnerability significantly affected trust and privacy concerns; and information processing control did not significantly affect privacy concerns. The relationship between trust and privacy concerns, and sustainable usage intention was statistically significant; and the relationship between trust and expansion of communication channels was also statistically significant.

• Journal of Information Processing Systems
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• 제11권1호
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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.