• Journal of the Ergonomics Society of Korea
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• v.29 no.4
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• pp.521-525
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• 2010

UX (User Experience) Design was an interdisciplinary approach in humanities, engineering, science and design. We classified the roles of user experience; requirement analysis which are user research, constraints analysis and direction analysis, concept design, information architecture, physical UI, graphical UI, sound UI, Olfactory UI, prototype, evaluation, launch, localization, and knowledge management/UI DB. User research methods were classified by the relation of designer, user, and product/service. We reviewed three issues of UX design; complexity management, efficiency management, and mapping management.

• Journal of the Ergonomics Society of Korea
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• v.33 no.3
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• pp.175-189
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• 2014

Objective: The goal of this research is to develop new user behavior model using user motion analysis with microscopic perspective for attracting user's participation in interactive space. Background: The interactive space is 'human's place', which is made up of complex elements of digital virtual space and traditional analog and physical environment based on human-computer interaction system. Human behavior has changed in it at the same time. If the user couldn't make participation in interaction, the purpose of the system is not met, which reduces its effect. Therefore, we need to focus on interactive space that is potential future direction from a new point of view. Method: For this research, we would discuss and study fields of interactive space; (1) finding definition of interactive space and studying background of theory about it. (2) providing base of user behavior model with study of user's context that is to be user information and motion. (3) examining user motion, classify basic motion type and making user participation behavior model in phases. Results: Through this process, user's basic twenty motions which are systematized are taken as a standard for analysis of interaction process and participation in interactive space. Then, 'NK-$I^5$ (I Five)' model is developed for user participation types in interactive space. There are five phases of user participation behavior: Imperception, Interest, Involvement, Immersion, and Influence. In this analysis, three indicators which are time, motion types, and user relationship are found to be related to participation. Conclusion: The capabilities and limitation of this research is discussed to attract user participation. This paper focuses especially on contribution of design to lead user's participation in interactive system and expectation to help adapt to user centered design of various interactive space with new aspect of user behavior research. Application: The results of the 'NK-$I^5$ (I Five)' model might help to realize successful interactive space based on user centered design.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.124-131
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• 2020

As users of internet-based software applications increase, functional and non-functional problems for software applications are quickly exposed to user reviews. These user reviews are an important source of information for software improvement. User review mining has become an important topic of intelligent software engineering. This study proposes a user review mining method for software improvement. User review data collected by crawling on the app review page is analyzed to check user satisfaction. It analyzes the sentiment of positive and negative that users feel with a machine learning method. And it analyzes user requirement issues through topic analysis based on structural topic modeling. The user review mining process proposed in this study conducted a case study with the a non-face-to-face video conferencing app. Software improvement through user review mining contributes to the user lock-in effect and extending the life cycle of the software. The results of this study will contribute to providing insight on improvement not only for developers, but also for service operators and marketing.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.119-125
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• 2019

The purpose of this study is to find out the relevant factors of the choice tendency of tourism users to Intelligent Tourism platform through big data analysis, which will help enterprises to make accurate positioning and improvement according to user information feedback in the tourism market in the future, so as to gain the favor of users' choice and achieve long-term market competitiveness. This study takes the Intelligent Tourism platform as the independent variable and the user choice tendency as the dependent variable, and explores the related factors between the Intelligent Tourism platform and the user choice tendency. This study make use of text mining and R language text analysis, and uses SPSS and AMOS statistical analysis tools to carry out empirical analysis. According to the analysis results, the conclusions are as follows: service quality has a significant positive correlation with user choice tendency; service quality has a significant positive correlation with tourism trust; Tourism Trust has a significant positive correlation with user choice tendency; service quality has a significant positive correlation with user experience; user experience has a significant positive correlation with user choice tendency Positive correlation effect.

• Journal of Integrative Natural Science
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• v.14 no.2
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• pp.35-40
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• 2021

In this paper, we proposed a multi-subject-level sentiment analysis model for user reviews using the Latent Dirichlet Allocation (LDA) method targeting user-generated content (UGC). Data were collected from users' online reviews of hotels in major tourist cities in the world, and 30 hotel-related topics were extracted using the entire user reviews through the LDA technique. Six major hotel-related themes (Cleanliness, Location, Rooms, Service, Sleep Quality, and Value) were selected from the extracted themes, and emotions were evaluated for sentences corresponding to six themes in each user review in the proposed sentiment analysis model. Sentiment was analyzed using a dictionary. In addition, the performance of the proposed sentiment analysis model was evaluated by comparing the emotional values for each subject in the user reviews and the detailed scores evaluated by the user directly for each hotel attribute. As a result of analyzing the values of accuracy and recall of the proposed sentiment analysis model, it was analyzed that the efficiency was high.

• Design Convergence Study
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• v.16 no.5
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• pp.203-217
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• 2017

This study proposes and demonstrates the value of user - centered design methodology based on linguistic analysis. The results of the proposed user behavioural analysis framework suggested that the syntactic structure between the sentence structure and its components could be a logical basis for explaining the user's situation and behavior. Based on this, the definitions and classifications of user interactions and user contexts were conducted in a microscopically context. User behavior has also been established to identify pattern structures of purposeful nature and constitutes a user behavior sequence that prioritizes them. Next, the User Experience Analysis Framework was derived by defining the relationship between User Behavior and User Behavior and User Context and User Context. To verify the framework of the framework, a professional assessment was conducted to conduct a review of the user's experience and conduct a study of the framework of the framework and conduct of the framework of the framework of the framework and practical utility of the framework. Through this, it was possible to identify the value of the qualitative and quantitative framework of the framework and the future direction of development.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.131-142
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• 2021

Recently, there has been an active service that provides customized news to news subscribers. In this study, we intend to design a customized news service system through Deep Learning-based Social Network Service (SNS) activity analysis, applying real news and avoiding fake news. In other words, the core of this study is the study of delivery methods and delivery devices to provide customized news services based on analysis of users, SNS activities. First of all, this research method consists of a total of five steps. In the first stage, social network service site access records are received from user terminals, and in the second stage, SNS sites are searched based on SNS site access records received to obtain user profile information and user SNS activity information. In step 3, the user's propensity is analyzed based on user profile information and SNS activity information, and in step 4, user-tailored news is selected through news search based on user propensity analysis results. Finally, in step 5, custom news is sent to the user terminal. This study will be of great help to news service providers to increase the number of news subscribers.

• The Journal of Information Systems
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• v.32 no.3
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• pp.1-17
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• 2023

Purpose The proliferation of data on the internet has created a need for innovative methods to analyze user satisfaction data. Traditional survey methods are becoming inadequate in dealing with the increasing volume and diversity of data, and new methods using unstructured internet data are being explored. While numerous comment-based user satisfaction studies have been conducted, only a few have explored user satisfaction through video and audio data. Multimodal sentiment analysis, which integrates multiple modalities, has gained attention due to its high accuracy and broad applicability. Design/methodology/approach This study uses multimodal sentiment analysis to analyze user satisfaction of iPhone and Samsung products through online videos. The research reveals that the combination model integrating multiple data sources showed the most superior performance. Findings The findings also indicate that price is a crucial factor influencing user satisfaction, and users tend to exhibit more positive emotions when content with a product's price. The study highlights the importance of considering multiple factors when evaluating user satisfaction and provides valuable insights into the effectiveness of different data sources for sentiment analysis of product reviews.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.95-105
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• 2019

A great deal needs to be learned about why and how users participate and consume information on various online sites. The design of socio-technical systems especially for promoting engagement in terms of maximum user participation is both a theoretical and real-world challenge that researchers strive to understand. At present, most of the research on the motives of Internet video users' behavior focuses on the user's "viewing motivation" and "sharing motivation", and lacks the analysis of the factors affecting users' "subscription motivation". This study will attempt to compensate for this gap. Based on the YouTube platform, we take Chinese video users as the research object and uses the "Censydiam user motivation analysis model" to make assumptions about user subscription motivation from the two levels of social needs and personal needs, using regression analysis. Validate the hypothesis and get the influencing factors that may be available in the user's subscription motivation based on the assumptions. Built on survey data from 215 respondents, the study found that Enjoyment, Vitality, Power, and Conviviality are four factors that influence user motivation.

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.113-122
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• 2024

This comprehensive study delves into the analysis of user review data across various metaverse platforms, employing advanced text mining techniques such as TF-IDF and Word2Vec to gain insights into user perceptions. The primary objective is to uncover the factors that contribute to user satisfaction and dissatisfaction, thereby providing a nuanced understanding of user experiences in the metaverse. Through TF-IDF analysis, the research identifies key words and phrases frequently mentioned in user reviews, highlighting aspects that resonate positively with users, such as the ability to engage in creative activities and social interactions within these virtual environments. Word2Vec analysis further enriches this understanding by revealing the contextual relationships between words, offering a deeper insight into user sentiments and the specific features that enhance their engagement with the platforms. A significant finding of this study is the identification of common grievances among users, particularly related to the processes of refunds and login, which point to broader issues within payment systems and user interface designs across platforms. These insights are critical for developers and operators of metaverse platforms, suggesting a focused approach towards enhancing user experiences by amplifying positive aspects. The research underscores the importance of continuous improvement in user interface design and the transparency of payment systems to foster a loyal user base. By providing a comprehensive analysis of user reviews, this study offers valuable guidance for the strategic development and optimization of metaverse platforms, ensuring they remain responsive to user needs and continue to evolve as vibrant, engaging virtual environments.