• The Journal of Society for e-Business Studies
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• v.24 no.4
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• pp.49-78
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• 2019

In the context of knowledge sharing, network position has been a controversial subject. A central position in the network provides access to non-redundant knowledge, leading to more opportunities of knowledge sharing. On the other hand, as "bridging" relationships, its characteristics as a "weak tie" suggest innate lack of trust and reciprocity which is considered an impediment to share knowledge. This paper attempts to enlighten the underlying dynamic by examining the interaction between network centrality, motivation and ability in knowledge sharing. Furthermore, this paper examines the concept of knowledge sharing ability in depth by operationalizing the construct into three aspects: extensive and diverse knowledge, social media utilization ability and self-efficacy. The results show a partially supported three-way interaction, where the highest level of knowledge provision is reported when the employee has low network centrality, high autonomous motivation and high knowledge sharing ability, i.e. extensive and diverse prior knowledge. Though all models indicate strong associations between network centrality and knowledge sharing, this suggests an even greater power of motivation and ability that gives the strength to overcome unfavorable environments of peripheral position. Therefore, this paper offers an alternative explanation to the existing debate whether network centrality positively or negatively influences knowledge sharing.

• Educational Technology International
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• v.13 no.1
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• pp.175-205
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• 2012

The current study investigated whether SNS such as Twitter can be an assisting tool to compensate the limitations of online learning from social-affective and cognitive perspectives. Such limitations include low level of motivation to participate, feeling of isolation, rare exchanges of ideas and feedback from peers or instructors. This paper reports findings from a research study on the use of Twitter in online learning in Higher Education. Survey and subsequent interviews were conducted to examine students' perceptions about the cognitive and social-affective aspects of their participation in Twitter activities. Some of the challenges and potentials in integrating Twitter into online course are also addressed. It can be concluded that Twitter contributes not only to building close relationships among peers and instructors but also to opening a communication channel that can extend cognitive potentials.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.7
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• pp.297-306
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• 2019

This is a longitudinal study which aims to examine the effects of the use frequency of SNS on adolescents' stress and the relationship between the former and the latter, based on big five personality factors. To this end, the valid data of 994 adolescents were collected by administering questionnaires to the cohort groups of those using Facebook twice for one year(T1-T2). An analysis of the data showed that the use frequency of Facebook(T1) had no direct effects on stress(T2), and that there was an interaction between users' personality and the use frequency. In particular, users' stress(T2) was varied depending on neuroticism among personality factors, as the use frequency of Facebook(T1) increased. The higher the use frequency of Facebook, the more the stress in the group with weak neuroticism, while the higher the use frequency of Facebook, the less the stress in other group with strong neuroticism, probably because each group has different motivation for meeting their needs for social support: the former's stress may increase, since they has relatively lower needs for social support and face more conflicts as they more frequently use Facebook, while the latter's stress may decrease, because they have relatively stronger needs for social support and are likely to acquire psychological support, as they more frequently use it.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.221-228
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• 2016

This study was intended to investigate predictability among variables having an effect on problem solving skill and achievement in collaborative learning by utilizing SNS at university. To this end, 61 first-year students majoring in early childhood education at I community university in the national capital region were surveyed. And on the basis of the collected data, a multiple regression analysis was carried out. The results of carrying out the analysis are as follows. First, it was shown that self-efficacy, peer learning and help seeking had a significant effect on problem solving skill, and explained 70 of variability in problem solving skill. Second, it was shown that peek learning, help seeking and problem solving skill significantly predicted achievement, and explained 72% of the variability in achievement. Third, problem solving skill partially mediated the relationship between self-efficacy and achievement. The above-mentioned results imply that learning motivation should be increased so that learners have self-efficacy in order to improve college students' academic achievement in collaborative learning by utilizing SNS at university, and a class environment making it possible to actively provide peer learning and help seeking should be designed and a specific scheme enabling the enhancement of the problem solving skill should be considered.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.248-261
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• 2018

This study, the Fear of Missing Out Scale (FoMO Scale) developed by Przybylski et al. (2013) was adapted and validated to the Korean culture. 3-factors were constructed through EFA and item content analysis. In the CFA, 3 models were constructed to verify the fit of the model. Compared the goodness of fit, 3-factors model with 8 items proved to be the most appropriate. Sub-factors extracted through the characteristic context and rationale of Korean culture are 'belonging needs', 'extrinsic motivation', and 'relative deprivation'. K-FoMO scale and the reliability level of each sub-factor were good. Convergent validity was assessed by significant correlation the K-FoMO scores with life satisfaction, positive emotions, negative emotions, and SNS addiction proneness. Discriminant validity was assessed by low correlation with gratitude. At the end, limitation and suggestions for the future research were discussed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1069-1086
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• 2013

Nowadays, web defacement becomes the utmost threat which can harm the target organization's image and reputation. These defacement activities reflect the hacker's political motivation or his tendency. Therefore, the analysis of the hacker's activities can give the decisive clue to pursue criminals. A specific message or photo or music on the defaced web site and the outcome of analysis will be supplying some decisive clues to track down criminals. The encoding method or used fonts of the remained hacker's messages, and hacker's SNS ID such as Twitter or Facebook ID also can help for tracking hackers information. In this paper, we implemented the web defacement analysis system by applying CBR algorithm. The implemented system extracts the features from the web defacement cases on zone-h.org. This paper will be useful to understand the hacker's purpose and to plan countermeasures as a IDSS(Investigation Detection Support System).

• Journal of Digital Convergence
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• v.15 no.1
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• pp.97-108
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• 2017

Web 2.0 paradigm and technologies allow users to contribute their information voluntarily and actively to online community. This paper aims to investigate key determinants of information contribution in online communities. We come up with the research model and proposed hypotheses on the basis of intensive literature review on motivation theory, information literacy, and self expression. Using survey response date collected from those who have ever experienced in uploading or providing information on online community such as social media. A total of 262 survey responses were used to test research hypotheses. The results show that self expression motive influences on information representation capability(IRC) and information contribution. The impact of Information literacy on IRC is found to be significant, and IRC is positively related to information contribution. In addition, approval motive is proven to be key determinant of IRC and information contribution. Some practical implications of these findings are discussed.

• Journal of Information Technology Applications and Management
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• v.16 no.2
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• pp.45-63
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• 2009

China has the largest number of the user of web 2.0 such as messengers and blogs, as of 2008 year. Chinese Internet digital market will grow from $85 billion in 2007 to $264 billion in 2015. The importance of Chinese Internet business is increasing, because of its size and growth potential. This research is focused on following two questions. First, what are the major characteristics of social networking services in China? In order to find out the answer about this question, the case study on Tencent QQ and Sina Poco, the most representative social networking services company in China, was done. And the reason of the use of social networking services, their contents, and the attitude toward the paid service were identified. Second, what are the major factors influencing the use of social networking services in China. User participation, network effect, usefulness, and system quality were inferred as the factors influencing the use. These factors were based on motivation theory, technology acceptance model, and the related research papers. This research model was proved by data analysis using Partial Least Square. As results, the use of social networking services was influenced by usefulness, network effect, user participation, and system quality. But social influence was not significant of the use of social networking services.

• Journal of Korean Clinical Health Science
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• v.7 no.2
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• pp.1289-1297
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• 2019

Purpose: The purpose of this study was to investigate occupational therapy at M college in Changwon and the impact of smart phone use on the school life of college students and to help them find ways to further develop in the future. Methods; Data collection was conducted using questionnaires, and the questionnaires consisted of 152 total questions with 15 interpersonal questions, 23 problem solving skills, 43 self-efficacy, 16 class participation scale, and 55 self-directed learning scale. It was conducted to first and second graders of M college and conducted a survey through the corresponding academic year from March 26, 2019 to March 29, 2019 to retrieve 120 questionnaires and use them for analysis. The collected data were analyzed using SPSS. Statistic 20.0. Results: Studies show that "school life satisfaction" is usually the highest at 53 percent. The "smartphone user motivation" was the highest with 50.8 percent, while the "most frequently used feature on smartphones" was the highest with 57.5 percent on SNS. Satisfaction after using a smartphone was the highest with 49.2 percent, while 41.7 percent said it would be easier to acquire and utilize information in the areas of satisfaction. Conclusion: Smartphone addiction, interpersonal relationships, problem-solving skills, self-efficacy, participation in classes, and self-control learning items are not only affected by one part, but also by the other.