• Journal of Fisheries and Marine Sciences Education
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• v.25 no.2
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• pp.375-392
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• 2013

The This study attempted to analyze what perception and attitude teachers have on corporal punishment. For these purpose, 458 writings about corporal punishment that 140 teachers loaded on web-site were collected and were analyzed using qualitative content analysis. : First, each writing was open-coded according to specific theme or meaning relating to corporal punishment using Nvivo program. Second, coded materials were classified as a high category when having similar theme or meaning. As a result of this process, 2 highest categories, 6 high categories and 24 subcategories were yielded. Teachers with positive view on corporal punishment tend to think that corporal punishment has some educational values or usefulness and their views were classified as very positive view, limited-permissive view, and inevitable view. They thought that corporal punishment were closely related to teachers' authority. Teachers have negative views on corporal punishment on the basis that corporal punishment causes side effects, is contrary to essentials of education, violates human rights etc. Negative views that teachers have on corporal punishment were classified as absolutely negative view and negative view focused on side effects. They thought that corporal punishment were not related to teachers' authority. Comments have been made on positive view on corporal punishment from the perspective of reflective analysis and implications of the results on theory and practice were discussed with comments on research limitations.

• Journal of Contemporary Eastern Asia
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• v.18 no.2
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• pp.118-141
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• 2019

In South Korea, as awareness of gender equality increased since the 1990s, policies for gender equality and social awareness of equality have been established. Until recently, however, the gap between men and women in social and economic activities has not reached the globally desired level and led to social conflict throughout the country. In this study, we analyze the content of online news comments to understand the public perception of gender equality and the details of gender conflict and to grasp the emergence and diffusion process of emerging issues on gender equality. We collected text data from the online news that included the word 'gender equality' posted from January 2012 to June 2017 and also collected comments on each selected news item. Through text mining and the temporal semantic network analysis, we tracked the changes in discourse on gender equality and conflict. Results revealed that gender conflicts are increasing in the online media, and the focus of conflict is shifting from 'position and role inequality' to 'opportunity inequality'.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.718-732
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• 2020

Conducting sentiment analysis and opinion mining are challenging tasks in natural language processing. Many of the sentiment analysis and opinion mining applications focus on product reviews, social media reviews, forums and microblogs whose reviews are topic-similar and opinion-rich. In this paper, we try to analyze the sentiments of sentences from online webcast reviews that scroll across the screen, which we call live barrages. Contrary to social media comments or product reviews, the topics in live barrages are more fragmented, and there are plenty of invalid comments that we must remove in the preprocessing phase. To extract evaluative sentiment sentences, we proposed a novel approach that clusters the barrages from the same commenter to solve the problem of scattering the information for each barrage. The method developed in this paper contains two subtasks: in the data preprocessing phase, we cluster the sentences from the same commenter and remove unavailable sentences; and we use a semi-supervised machine learning approach, the naïve Bayes algorithm, to analyze the sentiment of the barrage. According to our experimental results, this method shows that it performs well in analyzing the sentiment of online webcast barrages.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.10
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• pp.189-200
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• 2022

The gig economy offers many advantages, such as flexibility, variety, independence, and lower cost. However, there are also safety concerns, lack of regulations, uncertainty, and unsatisfactory services, causing people to voice their opinion on social media. This paper aims to explore the sentiments of consumers concerning gig economy services (Grab, Foodpanda and Airbnb) through the analysis of social media. First, Vader Lexicon was used to classify the comments into positive, negative, and neutral sentiments. Then, the comments were further classified into three machine learning algorithms: Support Vector Machine, Light Gradient Boosted Machine, and Logistic Regression. Results suggested that gig economy services in Malaysia received more positive sentiments (52%) than negative sentiments (19%) and neutral sentiments (29%). Based on the three algorithms used in this research, LGBM has been the best model with the highest accuracy of 85%, while SVM has 84% and LR 82%. The results of this study proved the power of text mining and sentiment analysis in extracting business value and providing insight to businesses. Additionally, it aids gig managers and service providers in understanding clients' sentiments about their goods and services and making necessary adjustments to optimize satisfaction.

• Asia pacific journal of information systems
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• v.31 no.4
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• pp.491-526
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• 2021

Airlines can employ a variety of quality monitoring procedures. In this study, we employ a content analysis of 8 years of online reviews for Korean airlines in contrast to other international airlines. Online airline reviews are infrequent, relative to the total number of passengers - the number of reviews is multiple orders of magnitude lower than passenger volumes - and online airline reviews are, therefore, not representative of passenger attitudes overall. Nevertheless, online reviews may be indicative of specific service issues, and draw attention to aspects that require further study by airline operators. Furthermore, significant words and phrases used in these airline reviews may help airline operators to rapidly automate filtering, partitioning, and analysis of incoming passenger comments via other channels, including email, social media posts, and call center transcripts. The current study provides insights into the contents of online reviews of Korean vs Other-International airlines, and opportunities for service enhancement. Further, we provide a set of marker words and phrases that may be helpful for management dashboards that require automated partitioning of passenger comments.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.835-844
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• 2009

In this study, a database composed by 46 cases of tunnel collapses has been built up. Based on the database, comprehensive data analysis is carried out, providing us a number of the technical lessons, which can be considered in future design and construction to minimize possibility of tunnel collapse disaster. For making a better understanding, the technical lessons are given in two divisions: mountain tunnel and urban tunnel. Tunnel collapses taking place in the former tunnel are generally due to bad discontinuity condition of jointed rock mass. Otherwise, urban tunnel has weak condition generally on ground water and weathering of ground. Most of technical comments given in this paper are made based on the cases of tunnel collapses only used in this study, so that the comments seems to be hard to be available to all the tunnelling cases. However, the comment should be valuable technical lessons for tunnel engineers to consider in tunnel design or construction.

• Korea Journal of Hospital Management
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• v.4 no.2
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• pp.60-84
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• 1999

Hospitals under competitive environment are getting more interested in PR(public relations) as a means of marketing. A typical form of public relations for the hospital is publicity, and its principal instrument is the press release that provides the mass media with the raw material and background for a news story. The purpose of this paper is to examine and analyze the public relations articles associated with hospitals in the section of health care in major daily newspapers. Three major daily newspapers, Chosun, Joongang and Hankyoreh have been analyzed for a year from January 1, 1998 to December 31, 1998. All articles in the health care section are classified by content, size, press comments, and style. This study has found some perverse aspects of the public relations such as the preponderance of health articles on tertiary medical institutions, inappropriate publicity focused on certain medical treatments, doctors, and hospitals, and the positive press comments on the hospitals that are affiliated with the same corporate group as the newspaper.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.9-15
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• 2018

Policy polls, which investigate the degree of support that the policy has for policy implementation, play an important role in making decisions. As the number of Internet users increases, the public is actively commenting on their policy news stories. Current policy polls tend to rely heavily on phone and offline surveys. Collecting and analyzing policy articles is useful in policy surveys. In this study, we propose a method of analyzing comments using deep learning technology showing outstanding performance in various fields. In particular, we designed various models based on the recurrent neural network (RNN) which is suitable for sequential data and compared the performance with the support vector machine (SVM), which is a traditional machine learning model. For all test sets, the SVM model show an accuracy of 0.73 and the RNN model have an accuracy of 0.83.

• Journal of Fashion Business
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• v.26 no.6
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• pp.116-132
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• 2022

Fashion marketing activity performed by social media influencers (SMIs) has grown exponentially in the past years. Research regarding their marketing power is often discussed in the context of sponsorship disclosure, in order to overcome obstacles of impending regulations that may endanger the authenticity SMIs are perceived to have compared to traditional marketing agents. Upon recent heterogeneous findings, a netnographic approach was taken to examine the actual sponsored posts of SMIs on Instagram. Based on two representative cases that received media coverage, a qualitative analysis of 1,058 comments on Instagram showed customer inspiration and informational social influence regardless of sponsorship disclosures present. Regarding customer inspiration, high frequency of comments including choice imitation intentions was observed. Under certain conditions, customer responses were focused on the SMI's expertise irrespective from the brand being endorsed. Findings show future implications from both an academic and industry-focused perspective for future potential of SMIs in fashion marketing.

• Asia pacific journal of information systems
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• v.30 no.2
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• pp.420-438
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• 2020

Recently, with the advance of the wireless Internet access via mobile devices, a myriad of game development companies have forayed into the mobile game market, leading to intense competition. To survive in this fierce competition, mobile game developers often try to get a grasp of the rapidly changing needs of their customers by operating their own official communities where game users freely leave their requests, suggestions, and ideas relevant to focal games. Based on the heuristic-systematic model (HSM) and the data quality (DQ) framework, this study derives key content, non-content, and hybrid cues that can be utilized when game developers accept suggested postings in these online communities. The results of hierarchical multiple regression analysis show that relevancy, timeliness, amount of writing, and the number of comments are positively associated with mobile game developers' knowledge adoption. In addition, title attractiveness mitigates the relationship between amount of writing/the number of comments and knowledge adoption.