• The Journal of Korean Medicine
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• v.44 no.4
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• pp.121-135
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• 2023

Objectives: This study aimed to establish and provide reliable information for general public, based on expert consensus, on the risks of misuse of medicinal herbs for food and pure food ingredients for the fetus during pregnancy. Methods: A panelist of seven traditional Korean medicine (TKM) gynecologists responded to a questionnaire summarizing the fetal safety literature for twenty-five medicinal herbs for food and pure food ingredients derived from medicated diet (藥膳, Yaksun) recipes during three online Delphi rounds anonymously. Results: Ginkgonis Semen (Ginkgo nut), Illici Veri Fructus (Star anise), lavender, bitter gourd, and parsley were agreed at the level 1 of "Do not consume". These five ingredients were recognized as having significant risks both in the literature evidence and in expert opinion. Rosemary, Citri Unshius Pericarpium, Discoreae Rhizoma, lemongrass, Schisandrae Fructus, Cassiae Semen, Foeniculi Fructus, Mori Fructus, Cinnamomi Cortex, and Astragali Radix were agreed at the level 2 of "consultation with TKM practitioner is required". Conclusion: Based on the consensus of a seven-member expert panel of TKM gynecologists, consumption of Ginkgonis Semen (Ginkgo nut), Illici Veri Fructus (Star anise), lavender, bitter gourd, and parsley should be avoided by pregnant women. For Rosemary, Citri Unshius Pericarpium, Discoreae Rhizoma, lemongrass, Schisandrae Fructus, Cassiae Semen, Foeniculi Fructus, Mori Fructus, Cinnamomi Cortex, and Astragali Radix, the level 2 advisory may be recommended to use with caution and to consult a TKM practitioner for advice on consumption, dose, and duration.

• 한국체육학회지인문사회과학편
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• v.56 no.2
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• pp.303-320
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• 2017

This paper seeks to better understand the focal issues and persons related to Rio Olympic soccer games through social data science and analytics. This study collected its data from online news articles and comments specific to KOR during the Olympic football games. In order to investigate the public interests for each game and target persons, this study performed the co-occurrence words analysis. Then after, the study applied the NodeXL software to perform its visualization of the results. Through this application and process, the study found several major issues during the Rio Olympic men's football game including the following: the match between KOR and PIJ, KOR player Heungmin Son, commentator Young-Pyo Lee, sportscaster Woo-Jong Jo. The study also showed the general public opinion expressed positive words towards the South Korean national football team during the Rio Olympics, though there existed negative words as well. Furthermore the study revealed positive attitude towards the commentators and casters. In conclusion, the way to increase the public's interest in big sporting events can be achieved by providing the following: contents that include various professional sports analysis, a capable domain expert with thorough preparation, a commentator and/or caster with artistic sense as well as well-spoken, explanatory power and so on. Multidisciplinary research combined with sports science, social science, information technology and media can contribute to a wide range of theoretical studies and practical developments within the sports industry.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.139-152
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• 2013

Although a series of studies shows the fact that a company's reputation could affect its sales rate and stock price, due to the increased use of SNS, the research related to the online measurement method for the corporate reputation has been relatively insufficient. This study explores a design for a method to quantify the corporate reputation value by reconstructing the discussions in literature review. Concretely, this study divides the corporate reputation value into the corporate identity information and the corporate awareness information, which includes the following five sub-categories: (1) the quality of product and service; (2) the employment environment; (3) the corporate vision; (4) the social responsibility; and (5) the business achievement. Additionally, for the corporate identity assessment, this study considers the following six factors: (1) Agreeableness (Goodness), (2)Capability (Ability), (3)Enterprise (Rise), (4)Chic (Class), (5) Ruthlessness (Authority), and (6)Informality. Based on these categories and factors, this study develops a technique quantifying the corporate reputation value by selecting 'word items' for the reputation search, and after conducting a frequency analysis in a survey. Also, to verify the result, this study exemplifies the reputation of three SI companies in Korea which could be utilized by using the commercialized reputation service. This study firstly attempts the corporate reputation measurement by classifying the identity and the awareness (corporate image and communication) upon a company in detail and enables its real applicabilities by proposing a formula to measure the reputation scores which can be utilized by verified word items from a frequency analysis.

• Informatization Policy
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• v.30 no.2
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• pp.22-45
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• 2023

In research on the use of AI-based voice assistant services, problems related to the user's trust and privacy protection arising from the experience of service use are constantly being raised. The purpose of this study was to investigate empirically the effects of individual trust in AI and online privacy concerns on the continued use of AI-based voice assistants, specifically the impact of their interaction. In this study, question items were constructed based on previous studies, with an online survey conducted among 405 respondents. The effect of the user's trust in AI and privacy concerns on the adoption and continuous use intention of AI-based voice assistant services was analyzed using the Heckman selection model. As the main findings of the study, first, AI-based voice assistant service usage behavior was positively influenced by factors that promote technology acceptance, such as perceived usefulness, perceived ease of use, and social influence. Second, trust in AI had no statistically significant effect on AI-based voice assistant service usage behavior but had a positive effect on continuous use intention. Third, the privacy concern level was confirmed to have the effect of suppressing continuous use intention through interaction with trust in AI. These research results suggest the need to strengthen user experience through user opinion collection and action to improve trust in technology and alleviate users' concerns about privacy as governance for realizing digital government. When introducing artificial intelligence-based policy services, it is necessary to disclose transparently the scope of application of artificial intelligence technology through a public deliberation process, and the development of a system that can track and evaluate privacy issues ex-post and an algorithm that considers privacy protection is required.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.395-404
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• 2015

This study is exploring objective awareness of literary therapy by consideration of popular perception about literary therapy through analysis of big data. The purpose of this study is the deduction of meaning information through analysis in the viewpoint of big data at online social network service(SNS) about 'literary therapy'. Accordingly, the main way of research became content analysis of keyword linked to literary therapy by utilizing opinion mining method related to text mining. The study mainly grasped 'literary therapy' and analyzed 'bibliotherapy' comparatively. The period of study was from Oct. 10th to Nov. 10th, 2014(during 30 days), and SNS such as blog or twitter became the subject of search. Through the result of study analysis, the conclusion that the spread of literary therapeutic prospect, structural harmony of literary therapeutic field, and the solidity of perceptional axis about literary therapy are needed can be drawn. This study is worthwhile because it can investigate popular awareness about literary therapy and can suggest alternative for invigoration of literary therapy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.345-351
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• 2020

Administrative agencies today are paying keen attention to big data analysis to improve their policy responsiveness. Of all the big data, news articles can be used to understand public opinion regarding policy and policy issues. The amount of news output has increased rapidly because of the emergence of new online media outlets, which calls for the use of automated bots or automatic document classification tools. There are, however, limits to the automatic collection of news articles related to specific agencies or departments based on the existing news article categories and keyword search queries. Thus, this paper proposes a method to process articles using classification glossaries that take into account each agency's different work features. To this end, classification glossaries were developed by extracting the work features of different departments using Word2Vec and topic modeling techniques from news articles related to different agencies. As a result, the automatic classification of newspaper articles for each department yielded approximately 71% accuracy. This study is meaningful in making academic and practical contributions because it presents a method of extracting the work features for each department, and it is an unsupervised learning-based automatic classification method for automatically classifying news articles relevant to each agency.

• Journal of Information Management
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• v.38 no.3
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• pp.183-209
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• 2007

The representative example of the business model on internet environment, the business of the Naver, Empas and Google which provides information retrieval service is the internet portal. The portal sites provide information retrieval service which provides users information what they want to find, that is a huge social contribution. The portal site which provides a search service leads much problems. Consequently, the regulation against information retrieval is asserted powerfully in spite of the public interest. Namely, the regulation regarding the search business owner is tried. Finally, portal business owner puts the social responsibility as OSP. But, there is a doubt that portal business owner who has much problem which occurred on the portal site indirectly has responsibility directly. That is duty on portal site owner the censorship on the contents transferred. So, this thesis researches on the social critical opinion relating with a information retrieval from the legal side against the problem of the Internet.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.123-136
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• 2017

The evaluation and analysis method of information system (IS) is studied from the system perspective, the user perspective, and the management viewpoint. The detailed analysis method performs qualitative evaluation by user questionnaire or expert opinion. In this study, Measures the productivity and the effect of building administrative information systems. In the previous study, qualitative productivity and universal effect indicators were used, but in this study, quantitative productivity indicators and indicators specific to administrative complaints were selected. KONEPS, an administrative service system, used electronic contract records and information recorded in the intermediate process. The information was converted into the number of days, and the productivity based on the input manpower was calculated. The effect analysis analyzed the questionnaire related to civil affairs, which is the goal of the administrative work system. Each factor was divided into reflective structural variable and formal structural variable, and internal consistency and multi-collinearity were diagnosed. In order to verify the model, the influence of the work was set as a hypothesis, the reliability was verified according to the descriptive statistics method, the influence was measured through the regression analysis, and the model was analyzed by the multiple regression model path coefficient. Model validation methods are Chi-square (df, p), RMR, GFI, AGFI, NFI, CFI and GFI as indicators according to CFA.

• Knowledge Management Research
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• v.25 no.2
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• pp.69-94
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• 2024

With the development of cyberspace and its increasing interaction with our daily lives, cybercrime has been steadily increasing in recent years and has become more prominent as a serious social problem. Notably, the "four major malicious cybercrimes" - cyber fraud, cyber financial crime, cyber sexual violence, and cyber gambling - have drawn significant attention. In order to minimize the damage of cybercrime, it's crucial to delve into the specifics of each crime and develop targeted prevention and intervention strategies. Yet, most existing research relies on indirect data sources like statistics, victim testimonials, and public opinion. This study seeks to uncover the characteristics and factors of cybercrime by directly interviewing suspects involved in 'copyright infringement', 'gambling' related to illicit online content, and 'pornography crime'. Through coding analysis and text mining, the study aims to offer a more in-depth understanding of cybercrime dynamics. Furthermore, by suggesting preventative and remedial measures, the research aims to equip policymakers with vital information to reduce the repercussions of this escalating digital threat.