• Journal of the Korea Convergence Society
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• v.10 no.8
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• pp.137-144
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• 2019

This paper deals with the longitudinal study on the supply & demand-side diversity of digital media service. The purpose of this study is to measure the diversity of contents supply and demand-side of digital media platform providers by longitudinal data and discuss the implication. In the approval and re-authorization of pay-TV broadcasters, there were attempts to measure diversity indicators as items to evaluate the publicness and public interest of broadcasting, but they are mainly limited to the method of measuring diversity in the short-term supply side. Thus researcher wants to confirm the evaluation of two aspects through this study. First, researcher proposes a demand-side measurement methodology that utilizes actual audience data from users, and second, a longitudinal evaluation methodology that evaluates long-term trends of diversity change. Researcher has secured the actual supply and demand data of the platform player and confirmed trends of longitudinal diversification indexing for 50 months from 2012 to 2017. Through this research, researcher expects that the supply and demand-side and the longitudinal diversity evaluation will be utilized in a balanced way of publicness and public interest evaluation of broadcasting.

• 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.