This study attempted to examine the structural characteristics of the social network of nursing units by dividing them into a job-related advice network and a friendship network, and to analyze the relationship between nurse organizational commitment and intent to leave. The subjects were 420 nurses working in 4 hospitals and 30 nursing units. Data were analyzed using UCINET 6.0, SPSS 20.0 and HLM 7.0. In job-related advice networks, degree centrality of head nurse contributed to organizational commitment. Network density contributed to intent to leave. In friendship networks, closeness centrality of head nurses and betweenness centrality of charge nurse contributed to organizational commitment. Density and betweenness centrality of charge nurses contributed to intent to leave. Accordingly, it is necessary to foster good relationships between nurses and to develop various types of strategies for building effective networks.
The Journal of the Institute of Internet, Broadcasting and Communication
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v.17
no.2
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pp.75-82
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2017
In this paper, we consider social network analysis that focuses on community detection. Social networks embed community structure characteristics, i.e., a society can be partitioned into many social groups of individuals, with dense intra-group connections and much sparser inter-group connections. Exploring the community structure allows predicting as well as understanding individual's behaviors and interactions between people. In this paper, based on the interaction information extracted from a real-life Bluetooth contacts, we aim to reveal the social groups in a society of mobile carriers. Focusing on estimating the closeness of relationships between network entities through different similarity measurement methods, we introduce the clustering scheme to determine the underlying social structure. To evaluate our community detection method, we present the evaluation mechanism based on the basic properties of friendship.
A blog is a personal website where its owner publishes his/her articles for others. A blog can have relationships with other blogs. In this paper, we define a network that is composed of blogs connected together with such relationships as a blog network. Blog networks can have two different propensities characterized by the articles published in the blogs: information-valued propensity and friendship-valued propensity. The degree of each propensity of a blog network plays an important role in deciding business policies for blog networks. In this paper, we address the problem of determining the degrees of two propensities of a given blog network. First, we determine the degree of the propensity of every relationship, a basic unit of a blog network, by using classification that is one of data mining functionalities. Then, by utilizing the result thus obtained, we compute the degrees of two propensities of the whole blog network. Also, we propose a method to solve the problem that the degree of propensities depends on the size of blog networks. To verify the superiority of the proposed approach, we perform extensive experiments using a huge volume of real-world blog data. The results show that our approach provides high accuracy of around 93% in determining the degrees of both propensities of relationships between arbitrary two blogs. We also verify the applicability of the proposed approach by showing that if determines the degrees of the information-valued and friendship-valued propensities correctly in real-world blog networks.
KSII Transactions on Internet and Information Systems (TIIS)
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v.13
no.10
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pp.5179-5196
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2019
To explore an effective non-invasion medical imaging diagnostics approach for hepatocellular carcinoma (HCC), we propose a method based on adopting the multiple technologies with the multi-parametric data fusion, transfer learning, and multi-scale deep feature extraction. Firstly, to make full use of complementary and enhancing the contribution of different modalities viz. multi-parametric MRI images in the lesion diagnosis, we propose a data-level fusion strategy. Secondly, based on the fusion data as the input, the multi-scale residual neural network with SPP (Spatial Pyramid Pooling) is utilized for the discriminative feature representation learning. Thirdly, to mitigate the impact of the lack of training samples, we do the pre-training of the proposed multi-scale residual neural network model on the natural image dataset and the fine-tuning with the chosen multi-parametric MRI images as complementary data. The comparative experiment results on the dataset from the clinical cases show that our proposed approach by employing the multiple strategies achieves the highest accuracy of 0.847±0.023 in the classification problem on the HCC differentiation. In the problem of discriminating the HCC lesion from the non-tumor area, we achieve a good performance with accuracy, sensitivity, specificity and AUC (area under the ROC curve) being 0.981±0.002, 0.981±0.002, 0.991±0.007 and 0.999±0.0008, respectively.
Journal of Korea Society of Digital Industry and Information Management
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v.10
no.1
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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.
The purpose of this study is to investigate the effects of employees who attend graduate school on the expansion of the knowledge sharing network in their company. For this purpose, the researchers chose 10 worker-graduate students and 75 members of company 'A' that they belong to and 107 members of university 'B' that they belong to, 172 members in total. 10 overlapped employee-students were excluded. The results of this study are summarized as follow: First, the personal relations of the employee-students enhanced after they have entered the graduate school. The score for the question was 3.85 out of 5 points. Second, the employee-students played the role of the knowledge bridge between company's co-worker network and graduate school's classmate network. It was confirmed that the density of the company's network was higher than the density of the connected network of the company and the graduate school. The analysis result confirmed that the difference of the two groups was significant. This means that the company carried out exchange with more members and therefore gained various kinds of knowledge. Also, in all types of network, the structural hole of the company network was lower than that of the connected network of the company and graduate school. The ANOVA test using QAP procedure confirmed that the difference of two groups was significant (friendship network F=1.2856, p<0.05; information network F=1.278, p<0.05; and trust network F=1.23, p<0.05). It means that the company not only gained the newly acquired knowledge by the knowledge bridge of the employee-students, but also was able to share it more effectively with members. Third and lastly, the employee-students share various information related to the organization, duties and roles rest in the company throughout break time, working hours and direct inquiries. This means that the employee-students contributed to the innovation of knowledge sharing in the company by sharing knowledge that they gained from the graduate school within the company.
Journal of the Korean Society for Library and Information Science
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v.54
no.2
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pp.299-322
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2020
The purpose of this study is to suggest reading education plan by exploring the characteristics of peer-relationship networks of elementary school students, and grasping the effects of those characteristics on the reading competencies. Social network analysis method was used, and centrality analysis, QAP correlation and QAP multiple regression analyses were conducted to examine the relationship between peers and reading competencies. The findings show that the help relationship rather than peer characteristics and friend relationship was related to reading competencies. However, since the friend relationship has an effect on the help relationship, it is also found that the relationship between the friend and the help relationship network should be considered in order to improve the reading competencies. This network analysis results are meaningful in reading education plan in the sense that they suggest a useful guideline for the formation of members ranging from individuals, small groups, to a whole class, and for periodical activities considering situation and learning purposes such as before, during, and after reading activities.
Social Network Service(SNS) indicates the service to promote mutual friendship built in online focused on social relation between people. While a demand and concern of the service gets higher now more than ever, there are a lack of the approach in aspect of both technology and service still. 'Facebook' is the most famous in the world and the biggest in user number among various social network service. We investigate the key factors of 'Facebook' based on the side of approach both technology and service. We observe the behavior of users who have rich experience on using the social network service to find it. The result of this study reveals that an asynchronous method related to the technology drive to improve a sociality in social media. Furthermore, we find that openness connected with the technology force to intent the closed attribute in service through user observation. It is the unique qualities social media holds. The successful social network service can be expected if social media are developed to concern these factors.
The Journal of Korean Academic Society of Nursing Education
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v.30
no.2
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pp.182-191
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2024
Purpose: The purpose of this study was to explore the characteristics of social networks among registered nurses in acute nursing care units. Methods: This study used a survey design. Four nursing units from two acute hospitals were selected using a convenience method, and 83 nurses from those nursing units participated in the study in July 2022. The positive influences among nurses included friendship, collaboration, advice, and referent networks, and the negative influences included avoidance and bullying networks. Using the NetMiner program, the k-means clustering technique was applied to create groups of nodes with similar characteristics. The general characteristics of the participants were analyzed by mean, standard deviation, frequency, and ANOVA or chi-squared test. Results: As a result of dividing the 83 nurse participants into four clusters, positive influencers, silent peers, unwelcome peers, and active bullies were identified. Positive influence group nurses were frequently mentioned in the friendship, collaboration, advice, and referent networks. On the other hand, nurses in the unwelcome group and the active bullying group were frequently mentioned in the avoidance and bullying networks. Conclusion: Social networks that have a positive or negative impact on nursing performance are created through different relationships between nurses. Nurse managers can use the findings to create a more supportive and collaborative environment. Further research is needed to develop intervention programs to improve interactions and relationships between fellow nurses.
It is well known that smoking habit is hazardous to health, especially for juvenile. The present study on smoking behavior of high school students in Seoul has two major objectives. The first objective is to find out the smoking behavior of high school students in Seoul. Toward this objective, individual's smoking experience has been examined as ever smoking and never smoking. The second objective is to determine the variables associated with their smoking behavior at the individual, family and school environment levels. For the data collection, the survey was carried out for the four high schools in Seoul from September 15 through October 15, 1982. The major findings are summarized as follows: 1. Smoking behavior of the students 1) Out of 1,278 respondents, 30.2% of them were found to be current smokers and 29.3% of them were former smokers. This implies that around 60% of school students in Seoul have experienced smoking. 2) A significant differences in the current smoking rates between two types of the school students were shown as 19.3% for day-time school and 42% for night-time school. 3) In terms of the current smoking behavior, the students who don't live with parents were higher in smoking rate than those of the living with parents. 2. Attitudes and knowledge about smoking 1) Attitudes of students toward smoking in high school days were shown that around 17% of them agreed with it and around 64% of them disagreed with it. 2) Around 99% of the respondents answered that their smoking is harmful for health. A source of the information about negative effects of smoking on health was 'Radio and TV' (23.9%) as the most influential, 'school teacher' (20.9%), 'Newspaper' (18.2%) and so on. 3. Behavioral analysis for the current smokers 1) The factors affected for motivation in the first smoking were 'curiosity' (59.7%), 'temptation of friend' (19.7%), 'resistance feeling, (7.1%), 'merely interest and pleasure' (6%) respectively. 2) The time of the first smoking was 'third grade of Junior-high school' (31.5%) as highest, 'first grade of Senior-high school' (23.7%) and 'second grade of Junior-high school' (14.7%). 3) An average daily number of cigarettes consuming of current smokers was seven cigarettes. 4. Family and school-mates influences on individual's smoking behavior 1) The data revealed a significant relationship between student's smoking and their parent's smoking behavior. Around 75% of the students whom both parents are smoking have experienced cigarette smoking. It was found that the individual's smoking behavior was influenced by his sibling. Around 65% of the students whom brothers are smoking have experienced cigarette smoking. 2) The 'Smoking-Index' of friendship network or a group explained individual's smoking behavior in the group. The result of dyad analysis of smoking behavior in the friendship network showed that a high score of 'Smoking-Index' tended to be explained an adoption of smoking behavior at the individual level in the group. on the other hand, a low score of 'Smoking-Index' explained non-smoking behavior in the group.
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