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http://dx.doi.org/10.9723/jksiis.2018.23.2.063

Analysis of Trends in Science and Technology using Keyword Network Analysis  

Park, Ju Seop (동아대학교 경영문제연구소)
Kim, Na Rang (동아대학교 경영정보학과)
Han, Eun Jung (동아대학교 공동가치창출혁신연구소)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.23, no.2, 2018 , pp. 63-73 More about this Journal
Abstract
Academia and research institutes mainly use qualitative methods that rely on expert judgments to understand and predict research trends and science and technology trends. Since such a technique has the disadvantage of requiring much time and money, in this study, science and technology trends were predicted using keyword network analysis. To that end, 13,618 AI (Artificial Intelligence) patent abstracts were analyzed using keyword network analysis in three separate lots based on the period of the submission of each abstract: analysis period 1 (January 1, 2002 - December 31, 2006), analysis period 2 (January 1, 2007 - December 31, 2011), and analysis period 3 (January 1, 2012 - December 31, 2016). According to the results of frequency analyses, keywords related to methods in the field of AI application appeared more frequently as time passed from analysis period 1 to analysis period 3. In keyword network analyses, the connectivity between keywords related to methods in the field of AI application and other keywords increased over time. In addition, when the connected keywords that showed increasing or decreasing trends during the entire analysis period were analyzed, it could be seen that the connectivity to methods and management in the field of AI application was strengthened while the connectivity to the field of basic science and technology was weakened. According to analysis of keyword connection centrality, the centrality value of the field of AI application increased over time. According to analysis of keyword mediation centrality during analysis period 3, keywords related to methodologies in the field of AI application showed the highest mediation value. Therefore, it is expected that methods in the field of AI application will play the role of powerful intermediaries in AI hereafter. The technique presented in this paper can be employed in the excavation of tasks related to regional innovation or in fields such as social issue visualization.
Keywords
Keyword Network Analysis; Science and Technology Trends; AI (Artificial Intelligence); Keyword Degree Centricity Analysis; Keyword Betweenness Centricity Analysis;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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