Identification of Emerging Research at the national level: Scientometric Approach using Scopus

Yeo, Woon-Dong; Sohn, Eunsoo; Jung, Eui-Seob; Lee, Chang-Hoan

doi:10.1633/jim.2008.39.3.095

Cited by 5 publications

(3 citation statements)

References 20 publications

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“…They also offer such benefits as the division of the journals by topic and quotation information, which can be categorized by subject field through a co-citation analysis. Therefore, research tendencies can be visualized accordingly [ 36 , 37 ]. However, when analyses of co-appearing keywords in healthcare are conducted, it is common to use the PubMed database.…”

Section: Discussionmentioning

confidence: 99%

Social Network Analysis of Elders' Health Literacy and their Use of Online Health Information

Jang

2014

Healthc Inform Res

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ObjectivesUtilizing social network analysis, this study aimed to analyze the main keywords in the literature regarding the health literacy of and the use of online health information by aged persons over 65.MethodsMedical Subject Heading keywords were extracted from articles on the PubMed database of the National Library of Medicine. For health literacy, 110 articles out of 361 were initially extracted. Seventy-one keywords out of 1,021 were finally selected after removing repeated keywords and applying pruning. Regarding the use of online health information, 19 articles out of 26 were selected. One hundred forty-four keywords were initially extracted. After removing the repeated keywords, 74 keywords were finally selected.ResultsHealth literacy was found to be strongly connected with 'Health knowledge, attitudes, practices' and 'Patient education as topic.' 'Computer literacy' had strong connections with 'Internet' and 'Attitude towards computers.' 'Computer literacy' was connected to 'Health literacy,' and was studied according to the parameters 'Attitude towards health' and 'Patient education as topic.' The use of online health information was strongly connected with 'Health knowledge, attitudes, practices,' 'Consumer health information,' 'Patient education as topic,' etc. In the network, 'Computer literacy' was connected with 'Health education,' 'Patient satisfaction,' 'Self-efficacy,' 'Attitude to computer,' etc.ConclusionsResearch on older citizens' health literacy and their use of online health information was conducted together with study of computer literacy, patient education, attitude towards health, health education, patient satisfaction, etc. In particular, self-efficacy was noted as an important keyword. Further research should be conducted to identify the effective outcomes of self-efficacy in the area of interest.

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Section: Discussionmentioning

confidence: 99%

Social Network Analysis of Elders' Health Literacy and their Use of Online Health Information

Jang

2014

Healthc Inform Res

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“…Limiting the research scope to a number of influential journals can increase the reliability of the research outcome. Because these databases offer citation subject classification services, researchers use co-citation analysis to understand research trends within a given subject using social network analysis with cogitation analysis; thus, one can easily visualize research trends in a field [ 47 , 48 ]. However, health and medicine researchers have relied on the PubMed database to conduct co-word analyses of detailed subjects [ 2 , 13 ].…”

Section: Discussionmentioning

confidence: 99%

Application of Social Network Analysis to Health Care Sectors

Jang

Lee

2012

Healthc Inform Res

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ObjectivesThis study aimed to examine the feasibility of social network analysis as a valuable research tool for indicating a change in research topics in health care and medicine.MethodsPapers used in the analysis were collected from the PubMed database at the National Library of Medicine. After limiting the search to papers affiliated with the National Institutes of Health, 27,125 papers were selected for the analysis. From these papers, the top 100 non-duplicate and most studied Medical Subject Heading terms were extracted. NetMiner V.3 was used for analysis. Weighted degree centrality was applied to the analysis to compare the trends in the change of research topics. Changes in the core keywords were observed for the entire group and in three-year intervals.ResultsThe core keyword with the highest centrality value was "Risk Factor," followed by "Molecular Sequence Data," "Neoplasms," "Signal Transduction," "Brain," and "Amino Acid Sequence." Core keywords varied between time intervals, changing from "Molecular Sequence Data" to "Risk Factors" over time. "Risk Factors" was added as a new keyword and its social network was expanded. The slope of the keywords also varied over time: "Molecular Sequence Data," with a high centrality value, had a decreasing slope at certain intervals, whereas "SNP," with a low centrality value, had an increasing slope at certain intervals.ConclusionsThe social network analysis method is useful for tracking changes in research topics over time. Further research should be conducted to confirm the usefulness of this method in health care and medicine.

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“…국가 차원에서는 미래 사회의 비전 을 실현할 수 있도록 유망영역을 먼저 발굴하는 것 이 중요하다. 이러한 중요성을 인식하고 전 세계적 으로 유망기술 발굴에 대한 노력이 다양한 분야를 대상으로 지속되고 있다 [2,3] . Experts-based Expert panel, Delphi Experts can consider not only technological issues but also other key issues (environmental, social issues).…”

Section: ⅰ 서 론 급속도로 변화하는 과학기술 환경 속에서 국가와unclassified

Emerging Technologies in Mobile Communications for 2020

Lee¹,

Song²,

Han³

et al. 2013

The Journal of Korea Information and Communications Society

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Recently, it becomes essential for firms or nations to forecast the future and identify emerging technologies in order to improve R&D efficiency and gain a competitive advantage. Particularly, the mobile communications industry is characterized by rapid advance and wide application of its technology and thus identifying emerging technologies is more important in the industry than in others. Nevertheless, few attempts have been made to explore its emerging technologies. Therefore, this research aims to develop a methodology to identify the future and emerging technologies especially for the industry and applied it to list top ten emerging technologies for 2020 in the industry. For this purpose, firstly, we focused the key issues in the future targeting 2020 and identified user needs relating to them. Then, candidates of emerging technologies were defined from a set of technologies to meet the needs, for which technological and economic feasibility is assessed to determine their priorities. Finally, the top ten most important technologies were selected and verified. This research is distinct from the previous studies in that it takes a market-pull approach instead of a technology-push approach. The research results are expected to provide valuable information to support strategy-and policy-makings in the mobile communications industry.주저자：아주대학교 산업공학과,

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Identification of Emerging Research at the national level: Scientometric Approach using Scopus

Cited by 5 publications

References 20 publications

Social Network Analysis of Elders' Health Literacy and their Use of Online Health Information

Social Network Analysis of Elders' Health Literacy and their Use of Online Health Information

Application of Social Network Analysis to Health Care Sectors

Emerging Technologies in Mobile Communications for 2020

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