A Bibliometric Study of International and Domestic Academic Research on Intellectual property
Youngwoo Sohn1, Sanghyun Sung2
1Youngwoo Sohn, Department of Creative IT Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea, East Asian.
2Sanghyun Sung, Department of Postech Entrepreneurship Center, Pohang University of Science and Technology, Pohang, Republic of Korea, East Asian.
Manuscript received on 08 June 2019 | Revised Manuscript received on 14 June 2019 | Manuscript Published on 22 June 2019 | PP: 108-118 | Volume-8 Issue-8S2 June 2019 | Retrieval Number: H10210688S219/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Background/Objectives: This paper analyzes various intellectual property (IP) publications and predicts their research trends by constructing social networks from the representative international bibliographic databases. Methods/Statistical analysis: The research trends are then determined by using various social network analysis methods to analyze the relations between the research keywords. Specifically, this paper uses the socio-centric approach, which deals with the whole network, to analyze the overall research trends indicated by the research keywords, and the ego-centric approach to analyze emerging research trends in research keywords in order to identify the latest trend. Findings: The overall research trends in the International IP-Research Data analyzed that researchers are most active in researching EU Law, copyright infringement, and trademarks. The Korean Domestic IP-Research Data confirmed that infringement and protection of copyrights are the most common research topics in which researchers in Korea are actively involved. The Japanese Domestic IP-Research Data analyzed indicated that researchers in Japan are most active in researching intellectual property rights and laws. We conducted a linear regression analysis using LINEST function on the WDC Percentage to statistically analyze the annual research trends. The 10 research keywords with the highest positive LINEST values were then selected as the major emerging research keywords in the International, Korean domestic, and Japanese domestic IP-Research Data. Additionally, we then constructed an ego-centric network to analyze the 10 major emerging research keywords, and then we utilized the community method to group the emerging keywords in the established ego-centric network by their high relations. Improvements/Applications: The results presented in this paper can be used to establish policies on IP, suggest directions for academic research, explore promising research topics, and promote joint research.
Keywords: Intellectual property, Academic Research Trends, Bibliometric Study, Social Network Analysis, Bibliographic Database.
Scope of the Article: Big Data Analytics for Social Networking using IoT