• Korea Journal of Hospital Management
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• v.22 no.1
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• pp.51-60
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• 2017

목적: 보건의료 관리 분야의 진로는 급변하는 사회적 요구와 시대적 흐름에 발맞추어 다양한 형태로 변화하여 왔다. 본 연구에서는 학습 수요자 측면으로 교과과정에 대한 만족도와 보건의료 계열 취업에 영향을 미치는 요인을 분석하여 보건의료 계열 학과 학생들의 취업률을 향상시킬 수 있는 방안을 도출하고자 한다. 방법: 경기도 성남시 소재 보건의료 계열 학과 163명을 대상으로 2013년 5월 6일부터 5월 9일까지 설문조사를 거쳐 분석을 실시하였다. 결과: 성별에 따른 교육과정의 만족도는 통계적으로 유의하지 않았으나, 고학년으로 올라갈수록 교육과정에 대한 만족도가 낮은 것으로 분석되었다. 성별과 학년에 따라 자격증 취득 계획 여부는 통계적으로 유의한 차이를 보였다. 즉, 성별이 여학생이고 학년이 낮을수록 전공관련 자격증 취득 계획이 높았다. 전공관련 자격증 취득에 영향을 미치는 요인으로는 '성별', '학년(학번)', '보건의료계열 분야로의 취업 여부'가 유의하게 영향을 미치는 것으로 나타났다. 보건의료계열 취업 여부에 영향을 미치는 요인으로는 '교육과정 만족도', '전공관련 자격증 취득 계획'이 통계학적으로 유의하게 영향을 미치는 것으로 분석되었다. 결론: 보건의료관련 학과 학생들의 동일계열 취업률을 향상시키기 위해서는 전공관련 자격증 취득에 직접 간접적으로 영향을 미치는 학생들의 요구를 파악하여 교육과정에 반영하는 것이 중요할 것이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.397-400
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• 2022

본 연구에서는 소셜 네트워크 서비스(Social Network Service, SNS) 데이터로부터 약물 부작용 게시글을 추출하기 위한 순환 신경망(Recurrent Neural Network, RNN) 기반 분류 모델을 제안한다. 먼저, 처방 빈도가 높으며 게시글을 많이 확보할 수 있는 케토프로펜 약물에 대하여 국내 최대 소셜 네트워크 플랫폼인 네이버 블로그와 카페의 게시글(2005 년~2020 년)을 확보하고 최종 3,828 건을 분석하였다. 결과적으로 케토프로펜에 대한 3 종(약물, 부작용, 불용어)의 렉시콘을 정의하였으며 이를 기반으로 Bi-LSTM 분류모델 기준 87%의 정확도를 얻었다. 본 연구에서 제안하는 모델은 SNS 데이터가 약물 부작용 정보 획득을 위한 기존 (전자의무기록, 자발적 약물 부작용 보고 시스템 등) 자료원에 대한 보완적 정보원이 되며, 개발된 Bi-LSTM 분류모델을 통해 약물 부작용 게시글 추출의 편리성을 제공할 것으로 기대된다.

• Journal of applied mathematics & informatics
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• v.26 no.1_2
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• pp.337-347
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• 2008

Based on social welfare maximum theory, the optimal scale of power plants entering generation power market being is researched. A static non-cooperative game model for short-term optimization of power plants with different cost is presented. And the equilibrium solutions and the total social welfare are obtained. According to principle of maximum social welfare selection, the optimization model is solved, optimal number of power plants entering the market is determined. The optimization results can not only increase the customer surplus and improve power production efficiency, but also sustain normal profits of power plants and scale economy of power production, and the waste of resource can also be avoided. At last, case results show that the proposed model is efficient.

• Journal of the Korean Society for information Management
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• v.21 no.2
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• pp.23-44
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• 2004

This study proposed a theoretical framework that could explain the service use of a community informatics. The proposed community informatics use model was developed based on three theoretical models: (1) Ajzen's Theory of Planned Behavior (TPB) from social psychology: (2) Uses and gratifications approaches from media use research; and (3) Technology Acceptance Model(TAM) from information technology use research. The proposed model consists of three basic components: expectations of the outcomes from use, approvals from important others, and perceivied controllability over using the service. The initially proposed model was assessed using structural equation modeling, and then re-sepcified in order to propose a better fitting model. The initially proposed and revised community informatics use models were discussed with their theoretical and practical implications.

• Genomics & Informatics
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• v.18 no.2
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• pp.16.1-16.5
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• 2020

There has been a dramatic increase in the popularity of utilizing social media data for research purposes within the biomedical community. In PubMed alone, there have been nearly 2,500 publication entries since 2014 that deal with analyzing social media data from Twitter and Reddit. However, the vast majority of those works do not share their code or data for replicating their studies. With minimal exceptions, the few that do, place the burden on the researcher to figure out how to fetch the data, how to best format their data, and how to create automatic and manual annotations on the acquired data. In order to address this pressing issue, we introduce the Social Media Mining Toolkit (SMMT), a suite of tools aimed to encapsulate the cumbersome details of acquiring, preprocessing, annotating and standardizing social media data. The purpose of our toolkit is for researchers to focus on answering research questions, and not the technical aspects of using social media data. By using a standard toolkit, researchers will be able to acquire, use, and release data in a consistent way that is transparent for everybody using the toolkit, hence, simplifying research reproducibility and accessibility in the social media domain.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.540-557
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• 2021

Privacy vulnerability of social networks is one of the major concerns for social science research and business analysis. Most existing studies which mainly focus on un-weighted network graph, have designed various privacy models similar to k-anonymity to prevent data disclosure of vertex attributes or relationships, but they may be suffered from serious problems of huge information loss and significant modification of key properties of the network structure. Furthermore, there still lacks further considerations of privacy protection for important sensitive edges in weighted social networks. To address this problem, this paper proposes a privacy preserving method to protect sensitive weighted edges. Firstly, the sensitive edges are differentiated from weighted edges according to the edge betweenness centrality, which evaluates the importance of entities in social network. Then, the perturbation operations are used to preserve the privacy of weighted social network by adding some pseudo-edges or modifying specific edge weights, so that the bottleneck problem of information flow can be well resolved in key area of the social network. Experimental results show that the proposed method can not only effectively preserve the sensitive edges with lower computation cost, but also maintain the stability of the network structures. Further, the capability of defending against malicious attacks to important sensitive edges has been greatly improved.

• Journal of Information Science Theory and Practice
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• v.3 no.1
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• pp.50-65
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• 2015

Recently US/EU governments are utilizing nanotechnology as a key catalyst to support national innovation policies with economic recovery goals. US/EU nano policies have been serving as a global model to various countries, including Korea. So the authors initially seek to understand US/EU national innovation policy interconnections, and then find the role of nanotechnology development within. To strengthen national policy coherence, nanotechnology development strategies are under evolution as an innovation catalyst for promoting commercialization. To strategically support nano commercialization, EHS (Environmental, Health, Safety) and informatics are invested as priority fields to strengthen social acceptance and sustainability of nano enabled products. The current study explores US/EU national innovation policies including nano commercialization, EHS, and Informatics. Then obtained results are utilized to analyze weaknesses of Korean innovation systems of connecting creative economy and nanotechnology development policies. Then ongoing improvements are summarized focusing on EHS and informatics, which are currently prominent issues in international nanotechnology development.

• Genomics & Informatics
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• v.18 no.2
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• pp.17.1-17.4
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• 2020

The amount of content on social media platforms such as Twitter is expanding rapidly. Simultaneously, the lack of patient information seriously hinders the diagnosis and treatment of rare/intractable diseases. However, these patient communities are especially active on social media. Data from social media could serve as a source of patient-centric knowledge for these diseases complementary to the information collected in clinical settings and patient registries, and may also have potential for research use. To explore this question, we attempted to extract patient-centric knowledge from social media as a task for the 3-day Biomedical Linked Annotation Hackathon 6 (BLAH6). We selected amyotrophic lateral sclerosis and multiple sclerosis as use cases of rare and intractable diseases, respectively, and we extracted patient histories related to these health conditions from Twitter. Four diagnosed patients for each disease were selected. From the user timelines of these eight patients, we extracted tweets that might be related to health conditions. Based on our experiment, we show that our approach has considerable potential, although we identified problems that should be addressed in future attempts to mine information about rare/intractable diseases from Twitter.

• The Journal of Industrial Distribution & Business
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• v.13 no.9
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• pp.37-50
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• 2022

Purpose: The purpose of this study is to explore and compare research trends in Korea and overseas academic papers on social media marketing, and to present new academic perspectives for the future direction in Korea. Research design, data and methodology: We used English abstract of research paper (Korea's: 1,349, overseas': 5,036) for word frequency analysis, topic modeling, and trend analysis for each topic. Results: The results of word frequency and co-occurrence frequency analysis showed that Korea researches focused on the experiential values of users, and overseas researches focused on platforms and content. Next, 13 topics and 12 topics for Korea and overseas researches were derived from topic modeling. And, trend analysis showed that Korean studies were different from overseas in applying marketing methods to specific industries and they were interested in the short-term performance of social media marketing. Conclusions: We found that the long-term strategies of social media marketing and academic interest in the overall industry will necessary in the future researches. Also, data mining techniques will necessary to generate more general results by quantifying various phenomena in reality. Finally, we expected that continuous and various academic approaches for volatile social media is effective to derive practical implications.

• Journal of Information Technology Services
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• v.14 no.2
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• pp.337-354
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• 2015

In a day and age when contemporary businesses are transformed, driven by a service-dominance logic and dependent upon IT, we need to understand how firms cope with technological adaptations and how such technological adaptations can lead to service adaptations. Drawing on a framework on technological transitions and an interpretive longitudinal case study of the services provided by a team within a large public IT firm, this article addresses the following questions : How do service transitions come about? Can we distinguish particular patterns in service transition processes? This research unveils how technological and social dimensions mutually constitute each other within development and implementation of service provisioning. The findings show how：(a) IT plays a fundamental role in service provisioning; (b) technological transitions are the necessary but insufficient preconditions for service transitions; and (c) there are attenuation effects when it comes to the move from technology transition to service transition.