• Journal of Digital Convergence
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• v.14 no.11
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• pp.459-467
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• 2016

This study was conducted to evaluate and identify what factors influence the satisfaction of the users for the fast-growing social network game based on the mobile. To this end, we looked around the variable product characteristic factor, quality and the consumer characteristic factor, user self-determination. Also we surveyed 211 male and female college students. The first finding was that all the sub-factors of the quality factor had positive effects on the satisfaction of the mobile social network games. The second finding was that all the sub-factors of the self-determination factor had positive effects on the satisfaction of the mobile social network games. The third finding was that only the sub-factors of quality had positive relative effects on the satisfaction of the mobile social network games, in the order of playfulness, usability, functionality from the most to the least. The findings of this study are expected to offer meaningful and practical suggestions for the development of high quality game contents for the user convenience, as well as the academic significance, the expansion of game-related area of research through the break from the traditional research trends, technology and engineering point of view and from the PC-based online game.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.453-459
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• 2017

This study was conducted to review the usage behavior of mobile social network games that are attracting attention as a new growth engine in the game market. To that end, a survey was conducted on 250 male and female university students. The result of the study showed that first, the relationship formation motivation and seeking fun during leisure times in association with mobile social network games had a positive effect on game attitudes. Second, the relationship formation motivation had a positive effect on the continuous use intention. Third, the relationship formation motivation and the fun-seeking motivation had a positive effect on word-of-mouth recommendation, while the relationship formation motivation and advertisement recommendation motivation had a positive effect on the intention to recommendation online formats. Fourth, the attitude towards mobile social network games had a positive effect on the continuous use intention. Lastly, the attitude towards mobile social network games had a positive effect on only the intention to recommendation through word-of-mouth. This study is expected to provide useful and basic data for the development of quality game content that will cater to users' needs.

• Journal of Digital Convergence
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• v.18 no.4
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• pp.37-44
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• 2020

This study aimed to explore the relationship between Intelligent Robot Reacher(IRT)-student by examining the factors of their relationship perceived by middle school students. In doing so, we developed questionnaires based on the existing teacher-student relationship scale and conducted an online survey of 283 first graders in middle school. The collected date were analyzed using exploratory factor analyses with SPSS 23 and confirmatory factor analysis with Amos 21. The study findings identified four factors of IRT-student relationship namely "trust", "competence", "emotional exchange", and "tolerance". It is expected that the study can be used to discuss ways to enhance educationally significant interaction between students-IRT and teaching methods using intelligent robots(IRs). Also, the study will contribute to the understanding and development of various services using IRs. Based on the study finidngs, future studies should investigate the perception of various education stockholders (teachers, parets, etc) on IRT to elevate the Human-Robot Interaction in the education field.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.109-135
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• 2021

his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.