• The Journal of Information Systems
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• v.26 no.4
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• pp.107-135
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• 2017

Purpose Along with the growth of smart phones and social networking service (SNS), social commerce continues to expand. Although online reviews have become an important source of the information that consumers use to make purchasing decisions, theoretical development and empirical testing in this area are still limited. Thus, there is a need to develop further understanding about the influence of electronic word-of-mouth (eWOM). Drawing upon the heuristic - systematic model (HSM) which is one of the dual-process theories, this study develops a research model that explains key factors influencing consumers' eWOM credibility. Furthermore, this study verifies that consumer's eWOM credibility is a key determinant of eWOM and purchase intentions. Design/methodology/approach The proposed model is empirically tested with 493 users who have experience in WeChat-based social commerce. The structural equation model (SEM) analysis is used to evaluate the research model and hypotheses. Findings The major findings are as follows. First, argument quality of eWOM (a systematic factor) has a positive effect on eWOM credibility. Second, source credibility and recommendation consistency of eWOM (heuristic factors) are positively associated with eWOM credibility. Finally, purchase and eWOM intentions greatly depend on eWOM credibility. These results confirm the effectiveness of HSM in explaining eWOM mechanisms in SNS-based social commerce. The details of findings and implications are presented.

• Archives of design research
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• v.15 no.3
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• pp.137-148
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• 2002

As human-centered design has become new paradigm in the field of design, it is also needed to apply scenario-centered design methodology in planning and design new multi-media contents. In this paper, scenario-centered design process for multimedia contnets planning ＆ design was identified through a case study of contents design of internet shopping mall "Shop 'n' Chat". The study was preceded with three kinds of scenarios during design process, which are present situation scenario to find needed contents, behavior prototype scenario to make contents concrete, and future usage scenario to design visual interface. These three stages of scenario are exampled by of finally shopping scenario between 20's girls, internet shopping scenario with using messenger, and finally navigation/interaction scenario in future internet shopping mall.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.405-415
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• 2020

With the increase in smartphone user, mobile forensics has become an essential element in modern digital forensic investigation. Mobile messenger data is very important data in mobile forensics because it can acquire information such as user's life pattern and mental state. In order to analyze messenger data, a decryption technique of an encrypted messenger data is required. Since most messengers provide a message deleting function, a technique for recovering deleted messages is required. WeChat Messenger, a messenger used by about 1 billion people around the world, uses IMEI (International Mobile Equipment Identity) information to encrypt data and provides message deletion function. In this paper, we propose a data decryption method in the absence of IMEI information and propose a method for recovering deleted messages using FTS (Full Text Search) database created for full-text search function of SQLite database.

• Journal of Preventive Medicine and Public Health
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• v.51 no.6
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• pp.320-325
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• 2018

Objectives: This pilot study tested the effectiveness of a brief alcohol-related intervention delivered by the social media app WeChat to teach about ethanol-induced facial flushing and increase the willingness of students who see another student flushing to suggest that he or she should reduce or stop drinking. In the context of Chinese drinking culture, it is sometimes socially difficult to refuse a drink, even when experiencing physical discomfort, such as flushing. Methods: Classrooms of students in a medical university in China were randomly assigned to the intervention or control group. Students in the intervention group were invited to view 3 alcohol education lessons on WeChat during a 2-week period. A pretest and posttest before and after the 2-week period assessed changes in students' willingness to intervene if they saw someone flush while drinking. Data were collected about students' alcohol use and their ratings of the lessons. Results: Mixed-design analysis of variance yielded a significant time-by-treatment interaction effect on the variable of willingness to suggest that a flushing person stop or slow down their drinking, and the change was significant between the intervention and control groups. One-way analysis of covariance yielded a significant treatment effect at the posttest, after controlling for the pretest score. Students rated the lessons above the midpoint of the scale for being informative, interesting, and useful. Conclusions: The pilot study showed that a brief alcohol-related intervention delivered by WeChat could produce a measurable positive change in the willingness of university students to suggest that a student who flushes should stop drinking. This pilot study also suggested improvements for future lessons and evaluation design.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.15-31
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• 2023

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.205-210
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• 2024

Nowadays, online messengers are the main communication tool of modern people. Currently, not only messengers that communicate based on text and images, but also services that can interact in real time through voice or screen sharing are actively used by the MZs. This study aims to figure out 1) the motivation of users of voice chat services, and 2) to explore the influence of motivation for use on satisfaction that one of the factors that determine the user's experience. As a result, five major motivations for using voice chat service(Relationship formation, Usefulness, Relationship maintenance, communication supplementation, and distance overcoming) were found. Among them 'Usefulness' and 'Relationship maintenance had a positive effect on user satisfaction. This study, highlighted the various needs of users who communicate in a non-face-to-face environments as well as factors to be satisfied for their positive experiences. These results should be actively used in the online communications market.

• Information Systems Review
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• v.26 no.1
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• pp.119-149
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• 2024

This study investigates the antecedents and mechanisms influencing trust and behavioral intentions formation towards new AI chatbots, such as ChatGPT, as travel information searching services. Analyzing the roles of variables such as familiarity, novelty, personal innovativeness, information quality and perceived anthropomorphism, the research elucidates the impact of these factors on users' cognitive and affective trust, ultimately affecting their intention to adopt information and sustain the use of the AI chatbot. Results indicate that perceived familiarity and information quality positively influence both cognitive and affective trust, whereas perceived novelty contributes positively only to cognitive trust. Additionally, the personal innovativeness of new AI chatbot users was found to weaken the effect of familiarity on perceived trust, while the perceived level of anthropomorphism of the chatbot amplified the effects of novelty and familiarity on cognitive trust. These findings underscore the importance of considering factors such as familiarity, personal innovativeness, information quality and anthropomorphism in the design and implementation of AI chatbots, affecting trust and behavioral intention.

• Korean Journal of Applied Biomechanics
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• v.26 no.2
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• pp.183-190
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• 2016

Objective: The objective of this study is to present a scientific basis for ballet dancer training methods by analyzing the relationships between subjective assessment of the ballet movement 'Grand pas de chat' and kinematic and electromyographic factors. Method: The subjects were 14 professional dancers with 15 years of experience on average. Four cameras and a wireless electromyogram were used to examine kinematic factors, and the filmed videos were analyzed by 3 experts for subjective assessment. Results: Although no differences in kinematic factors were found between the excellent dancer group and the non-excellent dancer group divided based on the experts' assessment, some difference was found in electromyographic factors, especially in relation to the gastrocnemius muscle, rectus femoris muscle, and erector spinae muscle. A relationship between subjective assessment and kinematic and electromyographic factors was found, and factors such as right-side rectus femoris activation, time required, left-side gastrocnemius activation, and front-back displacement affected subjective assessment. Conclusion: This study showed a relationship between subjective assessment and kinematic and electromyographic factors. To receive higher scores in subjective assessment, it is necessary to extend the hang time by using the lower limb muscles. The findings of this study also indicate the necessity of weight training in order to improve dancing techniques.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2689-2694
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• 2012

In recent years, cyber crimes were intended to get financial benefits through malicious attempts such as DDoS attacks, stealing financial information and spam. Botnets, a network composed of large pool of infected hosts, lead such malicious attacks. The botnets have adopted several evasion techniques and variations. Therefore, it is difficult to detect and eliminate them. Current botnet solutions use a signature based detection mechanism. Furthermore, the solutions cannot cover broad areas enough to detect world-wide botnets. In this paper, we propose IRC (Internet Relay Chat) that is used to control the botnet communication in a session channel of IRC servers connected through the analysis of the relationship of the channel and the connection with the server bot-infected hosts and how to detect.

• Journal of Engineering Education Research
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• v.26 no.5
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• pp.17-28
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• 2023

Generative AI has arrived and it's here. Education, research, industry, and labor are all on edge about the changes it will bring. It is noteworthy that while there is a wide range of optimistic and pessimistic predictions about the impact of generative AI, there is more concern than hope when it comes to education. This paper focuses on the lack of discussion on the impact of AI in higher education. First, we reviewed the process of the emergence of generative AI and introduced how the impact of AI is being understood from various perspectives. Second, we classified work areas based on expertise and efficiency and analyzed the impact of AI on work in each area. Finally, the study found that the educational perception of generative AI and the way it is perceived for engineering education purposes can be very different. It also argued that there is a lack of active discussion and debate on areas that need to be specifically discussed around generative AI. This has led to a phenomenon known as professors' delayed indifference. We emphasized that it is time for a serious and realistic discussion on the connection and integration of AI and education.