• Journal of Information Technology Applications and Management
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• 제20권2호
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• pp.177-191
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• 2013

Social network has been expected to increase the value of social capital through online user interactions which remove geographical boundary. However, online users in social networks face challenges of assessing whether the anonymous user and his/her providing information are reliable or not because of limited experiences with a small number of users. Therefore. it is vital to provide a successful trust model which builds and maintains a web of trust. This study aims to propose a prediction method for the interpersonal trust which measures the level of trust about information provider in Facebook. To develop the prediction method. we first investigated behavioral research for trust in social science and extracted 5 antecedents of trust : lenience, ability, steadiness, intimacy, and similarity. Then we measured the antecedents from the history of interactive behavior and built prediction models using the two decision trees and a computational model. We also applied the proposed method to predict interpersonal trust between Facebook users and evaluated the prediction accuracy. The predicted trust metric has dynamic feature which can be adjusted over time according to the interaction between two users.

• Journal of Contemporary Eastern Asia
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• 제15권2호
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• pp.145-161
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• 2016

Using the Sunflower movement as a case study, this article seeks to articulate a theoretical framework to evaluate online "free spaces" as tools for political mobilization. To this end, this article conducts a thematic and content analysis of 151 posts on the official Facebook page of the Sunflower movement. Key results uncover four thematic functions among posts - expressive, informative, informative-support, and promotional - that overlap, in which the expressive theme prevails, and two thematic topics discussed by posts - damages by protesters and their ideology of freedom. I conclude that: (1) combining the logistic and thematic dimensions of posts enables a specific understanding of an online free space's political viability and anticipates the campaigns it will connect itself to; (2) the networked nature of the Sunflower movement page prompts the reconceptualization of (i) online free spaces as nodes through which various political campaigns and struggles are thematically connected by a political ideology; (ii) inactivity as a strategy where protest capital and followers accumulate to prepare and empower future mobilizations.

• 지식경영연구
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• 제13권2호
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• pp.1-18
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• 2012

This article describes how attributes of social network contribute to enhance innovativeness of corporation which is considered to be one of the competitive factors in this global market. The study especially focused on employees' formal and informal communication that is expected to play a mediating role between the factors. 211 employees were randomly selected to participate in an online survey. The result has shown that the static correlation exists between social network, communication, and innovativeness. Closeness of social network was the only influencing factor on communication and innovativeness, and had a partial mediated effect between social network and innovativeness. Based on the suggested contribution for HRD intervention, various communication channels should be developed and supported in order to enhance innovation among social networks in organizations.

• 디지털융복합연구
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• 제10권1호
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• pp.423-428
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• 2012

Web2.0시대로 바뀌면서 더 이상 사용자들은 정보를 수동적으로 소비하고 공유하던 것에서 스스로 정보를 창출, 교류하는 능동적인 형태로 변화하는 모습을 보이게 되었다. 국내 토종 SNS인 미투데이(me2day), 싸이월드(cyworld), (c)로그 및 국외 SNS인 페이스북(Facebook), 트위터(Twitter)의 사용자가 급증하고 있으며 FramVille, Mafia War's Game 등의 SNG에 많은 사용자들이 이용하고 있다. 국내의 SNG는 아직 국외에 비하여 활성화되고 있지 않는 단계이다. 이에 국내 게임 시장의 장점인 온라인 게임과 요즘 유행하고 있는 SNS 개념을 통합하여 국내 게임 시장에 맞는 새로운 형태의 게임 즉, SNOG(Social Network Online Game, 소셜 네트워크 온라인 게임)로의 발전 방향을 유연성의 확대, 접근성의 확대, 사회성의 확대의 3가지로 제시하고자 한다.

• 한국멀티미디어학회논문지
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• 제19권2호
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• pp.428-435
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• 2016

Hundreds of millions of new posts and information are being uploaded and propagated everyday on Online Social Networks(OSN) like Twitter, Facebook, or Instagram. This paper proposes and implements a GPS-location based SNS data mapping, analysis, and visualization system, called Smart SNS Map, which collects SNS data from Twitter and Instagram using hundreds of PlanetLab nodes distributed across the globe. Like no other previous systems, our system uniquely supports a variety of functions, including GPS-location based mapping of collected tweets and Instagram photos, keyword-based tweet or photo searching, real-time heat-map visualization of tweets and instagram photos, sentiment analysis, word cloud visualization, etc. Overall, a system like this, admittedly still in a prototype phase though, is expected to serve a role as a sort of social weather station sooner or later, which will help people understand what are happening around the SNS users, systems, society, and how they feel about them, as well as how they change over time and/or space.

• Asia pacific journal of information systems
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• 제34권2호
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• pp.635-660
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• 2024

A growing body of research explores how users of online communities navigate through large-scale platforms to find the information they seek. This study builds on the theories of homophily, structural embeddedness, and social exchange to investigate how interest homophily and existing communication structures serve as mechanisms driving information searches and the subsequent formation of communication networks in these communities. Specifically, we analyze comment-on-post tie formation using network data from "Today's House," the largest online user community specializing in interior design in Korea. Employing the LR-QAP method, a permutation-based hypothesis testing algorithm for social network data, our research identifies that network tie formation is driven by both homophilous information searches based on instrumental and hedonic interests, as well as by structurally induced searches such as preferential attachment, reciprocity, and transitivity. In addition, we investigate the contingent effects of communication structure on homophilous tie formation. Our findings suggest that while network-wide structural characteristics enhance homophilous tie formation based on instrumental interests, local network processes leverage homophily based on hedonic interests. We conclude by discussing the theoretical implications of the differential influence of participation motivations on information search patterns and the practical implications for the design of online communities.

• 여성건강간호학회지
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• 제30권2호
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• pp.140-152
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• 2024

Purpose: Social support is essential for postpartum well-being, but little is known about the postpnatal social support preferred by primiparous women. This study aimed to comprehensively understand and describe the meaning of postnatal social support experience in primiparous women. Methods: The participants were seven primiparous women who were within 1 year after childbirth, recruited through purposive and snowball sampling from an online parenting community. The data were collected through in-depth interviews from November 14 to 28, 2022. Participants were interviewed face-to-face or via phone or online platform, according to their choice. Colaizzi's phenomenological qualitative research method was applied to analyze the meaning of the participants' experience. Results: Five theme clusters and fourteen themes were identified from the data. The five theme clusters are as follows: (1) Shortcomings of the childbirth and postpartum care system I learned through my experience; (2) Government policies focusing on childbirth and child-rearing rather than postpartum recovery; (3) Driving force of postpartum recovery: Shared childbirth process; (4) Childcare on my own; and (5) Conflicted between being a stay-at-home mom and a working mom under inadequate maternity protection policies. Conclusion: Despite postpartum support from the government that was perceived as inadequate, first-time mothers regained confidence and motivation for parenting with the help of family, peers, and social networks. First-time mothers need support from professionals and reliable online communities for postpartum recovery and parenting.

• 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.

• 한국경영과학회지
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• 제34권3호
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• pp.1-27
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• 2009

Since online knowledge networks usually consist of a larger, loosely knit, and geographically distributed group of "strangers" who may not know each other very well, members may not willingly share their knowledge with others. In order to address this challenge, this study looks Into the factors that are expected to affect knowledge sharing in an online knowledge network. For empirical validation, we choose "the global network of Korean scientists and engineers (KOSEN)" as one of the best practices of online knowledge networks. By using the archival, network, and survey data, we validate two models of knowledge sharing in sequence (i.e., knowledge contribution and knowledge utilization models) and then discuss the results. The findings of this study show that individuals not only contribute but also utilize knowledge in an online knowledge network when they are structurally embedded and perceive a strong reciprocity. In the network. In addition, taking pleasure in helping is found to positively affect knowledge contribution, whereas perceiving usefulness is found to Influence knowledge utilization. Contributions of this study and future research opportunities are also discussed.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.101-106
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• 2023

In this busy world actually stress is continuously grow up in research and monitoring social websites. The social interaction is a process by which people act and react in relation with each other like play, fight, dance we can find social interactions. In this we find social structure means maintain the relationships among peoples and group of peoples. Its a limit and depends on its behavior. Because relationships established on expectations of every one involve depending on social network. There is lot of difference between emotional pain and physical pain. When you feel stress on physical body we all feel with tensions, stress on physical consequences, physical effects on our health. When we work on social network websites, developments or any research related information retrieving etc. our brain is going into stress. Actually by social network interactions like watching movies, online shopping, online marketing, online business here we observe sentiment analysis of movie reviews and feedback of customers either positive/negative. In movies there we can observe peoples reaction with each other it depends on actions in film like fights, dances, dialogues, content. Here we can analysis of stress on brain different actions of movie reviews. All these movie review analysis and stress on brain can calculated by machine learning techniques. Actually in target oriented business, the persons who are working in marketing always their brain in stress condition their emotional conditions are different at different times. In this paper how does brain deal with stress management. In software industries when developers are work at home, connected with clients in online work they gone under stress. And their emotional levels and stress levels always changes regarding work communication. In this paper we represent emotional intelligence with stress based analysis using machine learning techniques in social networks. It is ability of the person to be aware on your own emotions or feeling as well as feelings or emotions of the others use this awareness to manage self and your relationships. social interactions is not only about you its about every one can interacting and their expectations too. It about maintaining performance. Performance is sociological understanding how people can interact and a key to know analysis of social interactions. It is always to maintain successful interactions and inline expectations. That is to satisfy the audience. So people careful to control all of these and maintain impression management.