• Title/Summary/Keyword: Eigenvector methods

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A Study on the Perception of Quality of Care Services by Care Workers using Big Data (빅데이터를 활용한 요양보호사의 서비스질 인식에 관한 연구)

  • Han-A Cho
    • Journal of Korean Dental Hygiene Science
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    • v.6 no.1
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    • pp.13-25
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    • 2023
  • Background: This study was conducted to confirm the service quality management of care workers, who are direct service personnel of long-term care insurance for the elderly, using unstructured big data. Methods: Using a textome, this study collected and analyzed unstructured social data related to care workers' service quality. Frequency, TF-IDF, centrality, semantic network, and CONCOR analyses were conducted on the top 50 keywords collected by crawling the data. Results: As a result of frequency analysis, the top-ranked keywords were 'Long-term care services,' 'Care workers,' 'Quality of care services,' 'Long term care,' 'Long term care facilities,' 'Enhancement,' 'Elderly,' 'Treatment,' 'Improvement,' and 'Necessity.' The results of degree centrality and eigenvector centrality were almost the same as those of the frequency analysis. As a result of the CONCOR analysis, it was found that the improvement in the quality of long-term care services, the operation of the long-term care services, the long-term care services system, and the perception of the psychological aspects of the care workers were of high concern. Conclusion: This study contributes to setting various directions for improving the service quality of care workers by presenting perceptions related to the service quality of care workers as a meaningful group.

The Characteristics of a Research Network for Radiation Oncology in Korea (방사선종양학 분야의 연구 네트워크 특성 분석)

  • Choi, Jin-Hyun;Park, Seo-Hyun;Kang, Jin-Oh
    • Radiation Oncology Journal
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    • v.28 no.3
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    • pp.184-191
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    • 2010
  • Purpose: To evaluate the structural characteristics of a scientific network of radiation oncology society. Materials and Methods: A total of 1,512 articles published from 1986 to April 2010 with the terms 'radiation oncology' or 'therapeutic radiology' were obtained in the KoreaMed database. The co-authors were analyzed according to their affiliation, and their relationship was used to build a matrix. With the matrix, centralization indices and the Key Player index were analyzed. We used UCINET 6.0 for the network analysis, Netdraw for determining a sociogram and Key Player 1.44 for the key player analysis. Results: The centralization of the radiation oncology field decreased from 8.29% for the period from 1986~1990 to 1.84% from 2006~2010. However, when the Korean Journal of Medical Physics was excluded, centralization increased from 2.32% for the period from 2001~2005 to 3.80% from 2006~2010. This suggested that the communication in the clinical research field of radiation oncology is decreasing. In a node centralization analysis, Seoul National University was found to be the highest at 7.9%. Seoul National University showed the highest indices in the Outdegree (6.50%) and Indegree (8.54%), in addition to Betweenness (14.94%) and Eigenvector (135.234%). The Key Player analysis indicated that Inha University had the highest index at 0.491, but when the Korean Journal of Medical Physics was excluded, Yonsei University had the highest Key Player index at 0.584. Conclusion: The degree centrality in the network of radiation oncology decreased in the most recent period as more institutions are participating in network. However, the Betweenness centrality is still increasing, suggesting that the communications among research groups (clique) in radiation oncology is warranted.