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<P>This study investigated the individual and social determinants of the public’s phobia of infectious diseases in South Korea, where collective action was recently fueled by the public phobia over mad cow disease (bovine spongiform encephalopathy [BSE]). Gender-specific multivariate regression was used to compare the public perception of BSE and highly pathogenic avian influenza (HPAI). The analysis results differentiated between the determinants of the phobia for the 2 diseases, BSE and HPAI (N = 1002). As with HIV/AIDS and leprosy, the public fear of HPAI was expressed as a disease phobia that seeks to ensure the social exclusion of infection sources, whereas the fear of BSE was influenced by social and communication factors. Therefore, BSE, unlike previous HPAI, can be rapidly amplified amid the growing distrust in health communication, in which case the social determinants of disease phobia are associated with communicator trust, social values, and political attitude toward diseases rather than disease perception.</P>
<P>The present study investigates topic coverage and sentiment dynamics of two different media sources, Twitter and news publications, on the hot health issue of Ebola. We conduct content and sentiment analysis by: (1) applying vocabulary control to collected datasets; (2) employing the n-gram LDA topic modeling technique; (3) adopting entity extraction and entity network; and (4) introducing the concept of topic-based sentiment scores. With the query term 'Ebola' or 'Ebola virus', we collected 16,189 news articles from 1006 different publications and 7,106,297 tweets with the Twitter stream API. The experiments indicate that topic coverage of Twitter is narrower and more blurry than that of the news media. In terms of sentiment dynamics, the life span and variance of sentiment on Twitter is shorter and smaller than in the news. In addition, we observe that news articles focus more on event-related entities such as person, organization and location, whereas Twitter covers more time-oriented entities. Based on the results, we report on the characteristics of Twitter and news media as two distinct news outlets in terms of content coverage and sentiment dynamics.</P>
<P>This article examines three major characteristics—themes, research methods, and authorship—of Korean public administration research written in the Korean language during 1999 to 2009. It suggests that this research has evolved and advanced both quantitatively and qualitatively. Recent Korean scholarship can be characterized as consisting of more reform-oriented topics, more quantitative methods, and more diversified authorship. These characteristics were partially caused by increasing social demand for government reform and growing emphasis on methodological rigor in public administration research, as well as increased government research funding for graduate programs. This also concludes that the Korean public administration research has advanced greatly in past decades but needs a better thematic and methodological balance as well as balance between theoretical and prescriptive studies.</P>
<P>This study reviews research themes and methods used in information technology (IT) in government and e-government research. Although IT/e-government studies (including inward aspects of IT applications in government and e-government studies) continue to increase, they are not comprehensively understood as a subfield within public administration. Based on Rosenbloom’s three competing approaches to public administration (managerial, political, and legal), we investigated the major research themes of IT/e-government studies in public administration. We analyzed 248 IT/e-government articles published in six major public administration journals from 1965 to 2010 to examine IT/e-government research trends in terms of research themes and methods.</P>
<P>Although job satisfaction is a primary human resource management concern, there is little empirical research considering job satisfaction in non-Western countries. In Korea, reforms aim to make the public service more competitive and diverse and have led to the recruitment of more women and young people. This study uses data from the Korean Income and Labor Panel Study to explore the relationship of age, gender, and service sector with job satisfaction. No substantial difference was found in the perceived job satisfaction of public employees of different ages, but an unexpected negative association was found in a subsample of private employees. Korean public and nonprofit employees are more satisfied with their jobs than private employees are but are less satisfied with their wages than with job security and job content. The study supports the expectation hypothesis and suggests there is a gender effect on job satisfaction, particularly for wages and work environment.</P>
<P><B>Objective:</B></P><P>In current practice, medical experts use the pathological stage predictions provided in the Partin tables to support their decisions. Hence, the Partin tables are based on logistic regression built from the US data. In the present study, we developed a data-mining model to predict the pathologic stage of prostate cancer. In this newly developed model, using the classification and regression tree-particle swarm optimization analysis of the Korean population data, we aim to improve the prediction accuracy of the pathologic state of prostate cancer.</P><P><B>Method:</B></P><P>A total of 467 patients from the smart prostate cancer database were evaluated. The results were intended to predict the pathologic stage of prostate cancer: organ-confined disease and non–organ-confined disease. The accuracy of 4 classification and regression tree-particle swarm optimization models was compared; furthermore, the models were validated with the Partin tables using the receiver operating characteristic curve.</P><P><B>Results:</B></P><P>Among the 467 evaluated patients, 235 patients had organ-confined disease and 232 patients had non–organ-confined disease. The area under the receiver operating characteristic curve of the proposed classification and regression tree-particle swarm optimization model (0.858 ± 0.034) was larger than the 1 in the Partin tables (0.666 ± 0.046).</P><P><B>Conclusion:</B></P><P>The proposed classification and regression tree-particle swarm optimization model was superior to the Partin tables in terms of predicting the risk of prostate cancer. Compared to the validation of the Partin tables for the Korean population, the classification and regression tree-particle swarm optimization model resulted in a larger receiver operating characteristic curve and a more accurate prediction of the pathologic stage of prostate cancer in the Korean population.</P>
<P>This study investigated how infographics may affect individuals’ news processing, focusing on multimodality and interactivity as its signature characteristics. News readers’ prior knowledge and issue involvement, which affect their ability and motivation to process information, were considered as potential moderators. In a 3 (text vs graphic vs text + graphic) × 2 (hyperlinks vs no hyperlinks) between-subjects experiment (<I>N</I> = 360), participants read a news article concerning economic issues. Adding graphics to the news heightened the extent to which they engaged in news elaboration, albeit only among those with higher issue involvement. However, in-text hyperlinks hindered information recall among those with less prior knowledge, creating an information acquisition gap between more and less resourceful individuals. The graphical representation of news appeared to have heuristic appeals to those less involved in and less knowledgeable about the news topic, leading to more favorable news evaluation.</P>