• Journal of the Ergonomics Society of Korea
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• v.34 no.6
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• pp.563-581
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• 2015

Objective: This study was conducted to investigate the potential of sematic network analysis for design research. Background: As HCD (Human-Centered Design) was emphasized, lots of design research methodologies were developed and used in order to find user needs. However, it is still difficult to discover users' latent needs. This study suggests the semantic network analysis as a complementary means for design research, and proved its potential through the practical application, which compares multi-screen purchase and usage behaviors between America and China. Method: We conducted an in-depth interview with 32 consumers from USA and China, and analyzed interview texts through semantic network analysis. Cross cultural differences in purchase and usage behaviors were investigated, based on measuring centrality and community modularity of devices, functions, key buying factors and brands. Results: Americans use more services and functions in the multi-screen environment, compared to Chinese. As a device substitutes other devices, traditional boundaries of the devices are disappearing in the USA. Americans consider function to recall Apple, but Chinese consider function, design and brand to recall Apple, Sony and Samsung as an important brand at the time of their purchase. Conclusion: This study shows the potential of semantic network analysis for design research through the practical application. Semantic network analysis presents how the concepts regarding a theme are structured in the cognitive map of users with visual images and quantitative data. Therefore, it can complement the qualitative analysis of the existing design research. Application: As the design environment becomes more and more complicated like multi-screen environment, semantic network analysis, which is able to provide design insights in the intuitive and holistic perspective, will be acknowledged as an effective tool for further design research.

• Journal of Korea Trade
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• v.26 no.8
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• pp.37-57
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• 2022

Purpose -International diplomacy is key for the cohesive economic growth of countries around the world. This study aims to identify the major topics discussed and make sense of word pairs used in sentences by Chinese senior leaders during their diplomatic visits. It also compares the differences between key topics addressed during diplomatic visits to developed and developing countries. Design/methodology - We employed three methods: word frequency, co-word, and semantic network analysis. Text data are crawling state and official visit news released by the Ministry of Foreign Affairs of the People's Republic of China regarding diplomatic visits undertaken from 2015-2019. Findings - The results show economic and diplomatic relations most prominently during state and official visits. The discussion topics were classified according to nine centrality keywords most central to the structure and had the maximum influence in China. Moreover, the results showed that China's diplomatic issues and strategies differ between developed and developing countries. The topics mentioned in developing countries were more diverse. Originality/value - Our study proposes an effective approach to identify key topics in Chinese diplomatic talks with other countries. Moreover, it shows that discussion topics differ for developed and developing countries. The findings of this research can help researchers conduct empirical studies on diplomacy relationships and extend our method to other countries. Additionally, it can significantly help key policymakers gain insights into negotiations and establish a good diplomatic relationship with China.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.262-269
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• 2017

The purpose of this study is to provide direction of medical education by analysing medical school student's perception structure about 'happy doctor'. In particular, this study compared perception structure between two groups of students before clerkship and after clerkship. The subject of this study were 1~4 academic year students in medical school. Students' text about 'happy doctor' were collected by open-ended questionnaire and analyzed by using sematic network analysis. Based on the result of network analysis, perception structure of each groups were confirmed. The network of each groups have 'Professionalism' group including words such as 'patient', 'treatment', 'worthwhile' in common. Three groups, 'Professionalism', 'Quality of life' and 'Self-realization' constituted the before clerkship network. And five groups, 'Professionalism', 'Time with family', 'Balance between work and household', 'Interpersonal relationship', 'Physical and psychological health' constituted the after clerkship network. The results of this study is expected to contribute for developing the basic medical education curriculum for 'happy doctor'.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.139-150
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• 2021

Object orientation has become the predominant paradigm for conceptual modeling (e.g., UML), where the notions of class and object form the primitive building blocks of thought. Classes act as templates for objects that have attributes and methods (actions). The modeled systems are not even necessarily software systems: They can be human and artificial systems of many different kinds (e.g., teaching and learning systems). The UML class diagram is described as a central component of model-driven software development. It is the most common diagram in object-oriented models and used to model the static design view of a system. Objects both carry data and execute actions. According to some authorities in modeling, a certain degree of difficulty exists in understanding the semantics of these notions in UML class diagrams. Some researchers claim class diagrams have limited use for conceptual analysis and that they are best used for logical design. Performing conceptual analysis should not concern the ways facts are grouped into structures. Whether a fact will end up in the design as an attribute is not a conceptual issue. UML leads to drilling down into physical design details (e.g., private/public attributes, encapsulated operations, and navigating direction of an association). This paper is a venture to further the understanding of object-orientated concepts as exemplified in UML with the aim of developing a broad comprehension of conceptual modeling fundamentals. Thinging machine (TM) modeling is a new modeling language employed in such an undertaking. TM modeling interlaces structure (components) and actionality where actions infiltrate the attributes as much as the classes. Although space limitations affect some aspects of the class diagram, the concluding assessment of this study reveals the class description is a kind of shorthand for a richer sematic TM construct.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1807-1824
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• 2015

As the technologies advance, mobile peer-to-peer (MP2P) networks or systems become one of the major ways to share resources and information. On such a system, the information retrieval (IR), including the development of scalable infrastructures for indexing, becomes more complicated due to a huge increase on the amount of information and rapid information change. To keep the systems on MP2P networks more reliable and consistent, the index structures need to be updated frequently. For a semantic IR system, the index structure is even more complicated than a classic IR system and generally has higher update cost. The most well-known indexing technique used in semantic IR systems is Latent Semantic Indexing (LSI), of which the index structure is generated by singular value decomposition (SVD). Although LSI performs well, updating the index structure is not easy and time consuming. In an MP2P environment, which is fully distributed and dynamic, the update becomes more challenging. In this work, we consider how to update the sematic index generated by LSI and keep the index consistent in the whole MP2P network. The proposed Concept Space Update (CSU) protocol, based on distributed 2-Phase locking strategy, can effectively achieve the objectives in terms of two measurements: coverage speed and update cost. Using the proposed effective synchronization mechanism with the efficient updates on the SVD, re-computing the whole index on the P2P overlay can be avoided and the consistency can be achieved. Simulated experiments are also performed to validate our analysis on the proposed CSU protocol. The experimental results indicate that CSU is effective on updating the concept space with LSI/SVD index structure in MP2P semantic IR systems.