An Analysis of Overseas Research Trends on Driving Rehabilitation Simulator Using Text Mining

2021 ◽  
Vol 12 (6) ◽  
pp. 1141-1156
Author(s):  
Jaeyoung Lee ◽  
Byungyoon Chun ◽  
Chiangsoon Song
Keyword(s):  
2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 50-50
Author(s):  
Ha Neul Kim ◽  
Seok In Nam

Abstract Since 1980s professionals and social service providers have focused on aging at the place where people lived. This is the initial concept of the Aging in Place (AIP). Over 40 years, the topics have developed and extended to other disciplines welcoming different perspectives in the study of AIP. Therefore, this study aims to understand the overall research trends in Aging in Place (AIP) studies using text mining analysis to track the evolvement of AIP subtopics not only in Gerontology but also in various fields. To identify the topic trends, we collected the titles, abstracts, and keywords from 1,372 international articles that were published from 1981 to 2019. Then, keywords were extracted and cleaned based on precedent literature and discussions. We analyzed the keywords based on the degree of centrality and visualized the keyword-networks using VOSviewer and Pajek. Top-most popular keywords are “independent living”, “housing”, “older adults”, “home care”, “daily life activity” and “quality of life.” The change in topic trends shows that in the 1980s to early-2000s, research focused on organization and management level of intervention, home(housing) for the older adults, long term care. In the mid-2010s, health-related topics such as daily life activity, health service, health care delivery and quality of life have emerged. Recently, the topics have extended further to technology, caregiver, well-being, and environment design, environmental planning that support independent living of oneself. The research result shows that the interdisciplinary approach regarding AIP is not only inevitable but also encouraged for an in-depth discussion of the field.


2018 ◽  
Vol 96 ◽  
pp. 398-410 ◽  
Author(s):  
Zhikun Ding ◽  
Zongjie Li ◽  
Cheng Fan

2021 ◽  
Vol 12 (4) ◽  
pp. 2323-2336
Author(s):  
Boyeong Seo ◽  
Hyunchae Park
Keyword(s):  

Parasitology ◽  
2020 ◽  
Vol 147 (14) ◽  
pp. 1643-1657
Author(s):  
John T. Ellis ◽  
Bethany Ellis ◽  
Antonio Velez-Estevez ◽  
Michael P. Reichel ◽  
Manuel J. Cobo

AbstractBibliometric methods were used to analyse the major research trends, themes and topics over the last 30 years in the parasitology discipline. The tools used were SciMAT, VOSviewer and SWIFT-Review in conjunction with the parasitology literature contained in the MEDLINE, Web of Science, Scopus and Dimensions databases. The analyses show that the major research themes are dynamic and continually changing with time, although some themes identified based on keywords such as malaria, nematode, epidemiology and phylogeny are consistently referenced over time. We note the major impact of countries like Brazil has had on the literature of parasitology research. The increase in recent times of research productivity on ‘antiparasitics’ is discussed, as well as the change in emphasis on different antiparasitic drugs and insecticides over time. In summary, innovation in parasitology is global, extensive, multidisciplinary, constantly evolving and closely aligned with the availability of technology.


Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4621
Author(s):  
Zhikun Ding ◽  
Rongsheng Liu ◽  
Zongjie Li ◽  
Cheng Fan

The rapid increase in the number of online resources and academic articles has created great challenges for researchers and practitioners to efficiently grasp the status quo of building energy-related research. Rather than relying on manual inspections, advanced data analytics (such as text mining) can be used to enhance the efficiency and effectiveness in literature reviews. This article proposes a text mining-based approach for the automatic identification of major research trends in the field of building energy management. In total, 5712 articles (from 1972 to 2019) are analyzed. The word2vec model is used to optimize the latent Dirichlet allocation (LDA) results, and social networks are adopted to visualize the inter-topic relationships. The results are presented using the Gephi visualization platform. Based on inter-topic relevance and topic evolutions, in-depth analysis has been conducted to reveal research trends and hot topics in the field of building energy management. The research results indicate that heating, ventilation, and air conditioning (HVAC) is one of the most essential topics. The thermal environment, indoor illumination, and residential building occupant behaviors are important factors affecting building energy consumption. In addition, building energy-saving renovations, green buildings, and intelligent buildings are research hotspots, and potential future directions. The method developed in this article serves as an effective alternative for researchers and practitioners to extract useful insights from massive text data. It provides a prototype for the automatic identification of research trends based on text mining techniques.


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