• Asia pacific journal of information systems
• /
• v.21 no.1
• /
• pp.29-47
• /
• 2011

Despite the growing attention to the effective utilization of ICT system in workplace, there is an accumulation of evidence from the literature indicating that organizations do not utilize newly introduced ICT systems to their full functional potential and an amount of new implementations continue to fail. We explore the reasons for the underutilization of new ICT by focusing on the individuals' social networks. This paper investigates how the social networks influence individual adaptation to the new ICT and its related performance. Based on the coping theory, we establish a research model that explains the coping mechanism. Collected data are analyzed to test the proposed model and its hypotheses using PLS and UCINET. The results show that the coping effort mechanism of individuals can be explained in terms of their positions within social networks. We conclude the paper by discussing theoretical and practical implications for the research findings and by proposing future studies.

• Journal of Internet Computing and Services
• /
• v.10 no.3
• /
• pp.131-140
• /
• 2009

Recently, the information visualization research community has given significant attention to graph visualization, especially visualization of social networks. However, visualization of information flows in a very large social network has not been studied in depth. However, information flows are tightly related to the structure of social networks and it shows dynamic behavior of interactions between members of social networks. Thus, we can get much useful information about social networks from information flows. In this paper, we present our research result that enables users to navigate a very large social network in Google Maps' method and to take a look at information flows on the network. To this end, we devise three techniques; (i) mapping a very large social network to a 2-dimensional graph layout, (ii) exploring the graph to all directions with zooming it in/out, and (iii) building an efficient query processing framework. With these methods, we can visualize very large social networks and information flows in a limited display area with a limited computing resources.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.16 no.1
• /
• pp.21-35
• /
• 2021

Based on social capital theory, this study investigated the influence of the start-up founder's social competence on the start-up's access to funding sources and performance through the mediating role of the type of social network. This study aimed to examine two types of social networks empirically (i.e., personal networks and business networks) as social capital in analyzing the effect of the founder's social competence and social capital on the method of accessing funding sources. A self-report questionnaire was administered to 252 South Korean start-up founders whose businesses are based in South Korea. Path analysis and mediation effect analysis were performed by structural equation modeling(SEM) using STATA 16.1. This study examined the full mediating effect of the founder's social competence on his/her personal and business networks, respectively, and how the effect leads to different methods to approach funding sources. This is the first study in South Korea to analyze empirically how social competence has contrasting effects on personal and business networks as well as how each type of network varies in its influence on the method founders use to attract investment. This study is also significant in that it proposed a new methodology by utilizing the position generator as the measure of personal and business networks to analyze social networks in detail. The analyses of 252 survey data collected over a period of six months will be a valuable resource that may provide researchers, founders, investors, and other stakeholders in the start-up ecosystem with meaningful implications.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.39 no.3
• /
• pp.139-146
• /
• 2016

This study proposes a methodology to analyse social networks among participating design engineers during product development projects. The proposed methodology enables product development managers or the participating design engineers to make a proper decision on product development considering the performance of participating design engineers. It considers a product development environment where an integrated product data management (PDM) system manages the product development data and associated product development processes consistently in its database, and all the design engineers share the product development data in the PDM database for their activities in the product development project. It provides a novel approach to build social networks among design engineers from an operational product development data in the PDM database without surveys or monitoring participating engineers. It automatically generates social networks among the design engineers from the product data and relationships specified by the participants during the design activities. It allows analysts to gather operational data for their analysis without additional efforts for understanding complex and unstructured product development processes. This study also provides a set of measures to evaluate the social networks. It will show the role and efficiency of each design engineers in the social network. To show the feasibility of the approach, it suggests an architecture of social network analysis (SNA) system and implemented it with a research-purpose PDM system and R, a statistical software system. A product configuration management process with synthetical example data is applied to the SNA system and it shows that the approach enables analysts to evaluate current position of design engineers in their social networks.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.11
• /
• pp.5594-5615
• /
• 2019

Malicious social robots, which are disseminators of malicious information on social networks, seriously affect information security and network environments. The detection of malicious social robots is a hot topic and a significant concern for researchers. A method based on classification has been widely used for social robot detection. However, this method of classification is limited by an unbalanced data set in which legitimate, negative samples outnumber malicious robots (positive samples), which leads to unsatisfactory detection results. This paper proposes the use of generative adversarial networks (GANs) to extend the unbalanced data sets before training classifiers to improve the detection of social robots. Five popular oversampling algorithms were compared in the experiments, and the effects of imbalance degree and the expansion ratio of the original data on oversampling were studied. The experimental results showed that the proposed method achieved better detection performance compared with other algorithms in terms of the F1 measure. The GAN method also performed well when the imbalance degree was smaller than 15%.

• International Journal of Computer Science & Network Security
• /
• v.22 no.3
• /
• pp.396-404
• /
• 2022

Online social networks contain a large amount of data that can be converted into valuable and insightful information. Text mining approaches allow exploring large-scale data efficiently. Therefore, this study reviews the recent literature on text mining in online social networks in a way that produces valid and valuable knowledge for further research. The review identifies text mining techniques used in social networking, the data used, tools, and the challenges. Research questions were formulated, then search strategy and selection criteria were defined, followed by the analysis of each paper to extract the data relevant to the research questions. The result shows that the most social media platforms used as a source of the data are Twitter and Facebook. The most common text mining technique were sentiment analysis and topic modeling. Classification and clustering were the most common approaches applied by the studies. The challenges include the need for processing with huge volumes of data, the noise, and the dynamic of the data. The study explores the recent development in text mining approaches in social networking by providing state and general view of work done in this research area.

• Journal of Information Technology Services
• /
• v.19 no.1
• /
• pp.1-16
• /
• 2020

Suncheon City Regeneration Project is known as the concept of cultural residents. Through the previous projects, the residents' capabilities have been improved, and the projects have been carried out according to their strategies. For this reason, participants in urban regeneration projects are important. The purpose of this study is to actually identify the 'rescue center' and 'direct relationship' with the analysis utilizing the characteristics of social networks NetMiner solution of the participants, who led the project, Suncheon. Surveys and interviews were conducted for participants, and the characteristics of social networks were analyzed in time series to quantify and visualize the results. As a result of the analysis, social networks were changed among the participants before and after the urban regeneration project. Initially, loose networks were denser over time, and initially networks formed only around participants were expanded over time. Network analysis has revealed that the system is strengthening with urban regeneration projects in the form of public and public-private cooperation. This highlights the need for a city-centered urban regeneration strategy centered on people and shows that a dense network of participants can be a success factor.

• Korean Journal of Adult Nursing
• /
• v.27 no.2
• /
• pp.211-222
• /
• 2015

Purpose: This study was conducted to test the model for sleep in community-dwelling older adults. The hypothetical model based on a senescent sleep model was constructed using the multiple influencing factors of sleep and associated adverse outcomes of changes in sleep in the older adults. Methods: Data were collected from 203 community-dwelling older adults living in Korea, and analyzed using IBM SPSS 21.0 and AMOS 21.0. Results: Increased age and multiple comorbidities were associated with decreased physical activities. Decreased physical activities were associated with smaller social networks, and smaller social networks were associated with higher level of loneliness. Multiple comorbidities, decreased physical activities, larger social networks, and higher level of loneliness were associated with maladaptive sleep hygiene. Decreased physical activities, higher level loneliness, and shorter actual sleep duration were associated with worse sleep quality. Smaller social networks and shorter actual sleep duration were associated with lower cognitive functions. Smaller social networks, higher loneliness, and worse sleep quality were associated with more severe depressive symptoms. Conclusion: These findings suggest that the sleep improvement interventions not only with physical perspectives but psychosocial ones for older adults may improve depressive symptoms as well as sleep quality.

• ETRI Journal
• /
• v.43 no.5
• /
• pp.812-824
• /
• 2021

Recently, with an increase in Internet usage, users of online social networks (OSNs) have increased. Consequently, privacy leakage has become more serious. However, few studies have investigated the difference between privacy and actual behaviors. In particular, users' desire to change their privacy status is not supported by their privacy literacy. Presenting an accurate measurement of users' privacy status can cultivate the privacy literacy of users. However, the highly interactive nature of interpersonal communication on OSNs has promoted privacy to be viewed as a communal issue. As a large number of redundant users on social networks are unrelated to the user's privacy, existing algorithms are no longer applicable. To solve this problem, we propose a structural similarity measurement method suitable for the characteristics of social networks. The proposed method excludes redundant users and combines the attribute information to measure the privacy status of users. Using this approach, users can intuitively recognize their privacy status on OSNs. Experiments using real data show that our method can effectively and accurately help users improve their privacy disclosures.

• Knowledge Management Research
• /
• v.12 no.2
• /
• pp.69-80
• /
• 2011

This paper reports on a structural view of a knowledge network comprised of clubs and organisationsexpressly concerned with cultural activities in a regional Australian city. Social network analysis showed an uneven distribution of power, influence, and prominence in the network. The network structure consisted of two modules of vertices clustered around particular categories of creative arts and these modules were linked most frequently by several organisations acting as communication hubs and boundary spanners. The implications of the findings include 'network weaving' for improving the network structure and developing a systemic approach for exploring the structures of social action that form community-based knowledge networks.