• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.77-87
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• 2024

In this paper, we propose a study applying the Delphi technique to domestic blockchain experts to determine urgent and pivotal conditions for NFT proliferation. We examine these conditions from a PEST (Political, Economic, Social, and Technological Analysis of the Macro Environment) perspective, as well as the functions of digital assets (measurement, storage, and exchange). Through two rounds of expert surveys on the seven NFT perspectives, we identify 6 activating factors that can help guide future policy-making for the NFT market. These factors have broad implications for the development of new industries using blockchain technology and tokens. The Delphi method employed in this study is a group discussion technique that gathers opinions from experts anonymously through two rounds and to address drawbacks related to expert selection bias and opinion alignment, additional opinion collection and review of projections were conducted in each round.

• Asian Journal for Public Opinion Research
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• v.12 no.1
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• pp.53-74
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• 2024

The proliferation of health misinformation gained momentum amidst the outbreak of the novel coronavirus disease 2019 (COVID-19). People stuck in their homes, without work pressure, regardless of health concerns towards personal, family, or peer groups, consistently demanded information. People became engaged with misinformation while attempting to find health information content. This study used the content analysis method and analyzed 1,154 misinformation stories from four prominent signatories of the International Fact-Checking Network during the pandemic. The study finds the five main categories of misinformation related to the COVID-19 pandemic. These are 1) the severity of the virus, 2) cure, prevention, and treatment, 3) myths and rumors about vaccines, 4) health authorities' guidelines, and 5) personal and social impacts. Various sub-categories supported the content characteristics of these categories. The study also analyzed the emotional valence of health misinformation. It was found that misinformation containing negative sentiments got higher engagement during the pandemic. Positive and neutral sentiment misinformation has less reach. Surprise, fear, and anger/aggressive emotions highly affected people during the pandemic; in general, people and social media users warning people to safeguard themselves from COVID-19 and creating a confusing state were found as the primary motivation behind the propagation of misinformation. The present study offers valuable perspectives on the mechanisms underlying the spread of health-related misinformation amidst the COVID-19 outbreak. It highlights the significance of discerning the accuracy of information and the feelings it conveys in minimizing the adverse effects on the well-being of public health.

• Korean Journal of Clinical Pharmacy
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• v.27 no.4
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• pp.221-227
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• 2017

Background: As personalized healthcare industry has attracted much attention, big data analysis of healthcare data is essential. Lots of healthcare data such as product labeling, biomedical literature and social media data are unstructured, extracting meaningful information from the unstructured text data are becoming important. In particular, text mining for adverse drug reactions (ADRs) reports is able to provide signal information to predict and detect adverse drug reactions. There has been no study on text analysis of expert opinion on Korea Adverse Event Reporting System (KAERS) databases in Korea. Methods: Expert opinion text of KAERS database provided by Korea Institute of Drug Safety & Risk Management (KIDS-KD) are analyzed. To understand the whole text, word frequency analysis are performed, and to look for important keywords from the text TF-IDF weight analysis are performed. Also, related keywords with the important keywords are presented by calculating correlation coefficient. Results: Among total 90,522 reports, 120 insulin ADR report and 858 tramadol ADR report were analyzed. The ADRs such as dizziness, headache, vomiting, dyspepsia, and shock were ranked in order in the insulin data, while the ADR symptoms such as vomiting, 어지러움, dizziness, dyspepsia and constipation were ranked in order in the tramadol data as the most frequently used keywords. Conclusion: Using text mining of the expert opinion in KIDS-KD, frequently mentioned ADRs and medications are easily recovered. Text mining in ADRs research is able to play an important role in detecting signal information and prediction of ADRs.

• Asian Journal for Public Opinion Research
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• v.2 no.1
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• pp.8-14
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• 2014

The Chinese economic growth rate has been much higher than many countries of the world for many years now. Nowadays, China is experiencing significant economic transformation and structural adjustment. Its speed of development is slowing, and housing and commodity prices are slowly rising. Consequently, a series of economic and social problems have come into being. Under these circumstances, how satisfied are Chinese people on the seven aspects of daily living such as Housing Situation, Household Income, Health, Family Life, Food, Human Relations and Job? The Media and Public Opinion Research Center of Fudan University (FMORC) conducted a phone survey of 606 people living in Beijing, the capital and political and cultural center of China, and Shanghai, the Chinese economic center. The survey results show that the overall satisfaction of Chinese people with their daily life is high. The levels of Family Life and Human Relations are on the top, those of Food, Health and Jobs are listed from the third to the fifth, and satisfaction levels of their Housing Situation and Household Income are on the bottom. The satisfaction levels of males with their Family Life and Health are higher than those of females. Age has a significantly negative correlation with satisfaction with personal health. Monthly income has positive relationships with four aspects of daily life - house income, job, house situation, and family life. Owning a house in cities is another important factor that influences satisfaction with the house situation, house income, food, and family life. Shanghai residents also show higher satisfaction with their health than Beijing residents.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.845-854
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• 2016

Sentiment analysis or opinion mining is a technique of text mining employed to identify subjective information or opinions of an individual from documents in blogs, reviews, articles, or social networks. In the literature, only a problem of binary classification of ratings based on review texts in an online review. However, because there can be positive or negative reviews as well as neutral reviews, a multi-class classification will be more appropriate than the binary classification. To this end, we consider the multi-class classification of ratings based on review texts. In the preprocessing stage, we extract words related with ratings using chi-square statistic. Then the extracted words are used as input variables to multi-class classifiers such as support vector machines and proportional odds model to compare their predictive performances.

• Asian Journal for Public Opinion Research
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• v.9 no.2
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• pp.188-211
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• 2021

Decreasing response rates to traditional survey methods, like face-to-face and telephone interviews, have led survey practitioners around the world to seek new ways of conducting surveys in recent years." The COVID-19 pandemic exacerbated this problem because it made conducting face-to-face interviews even more difficult than before. For example, it made conducting face-to-face surveys infeasible in 2020 in South Korea, and so the Korean Academic Multimode Open Survey (KAMOS) was unable to conduct a planned face-to-face survey to recruit new panel members. The entire 8,514-member panel, established via two-stage probability-based sampling from 2016 to 2019, was invited to take three online/telephone surveys in 2020. Of these panel members, 1,352 responded to at least one survey in 2020. To test to what extent the panel remained representative of the adult South Korean population, we compared the two groups of panel members: those who responded to at least one survey in 2020 and those who did not. After weighting both groups on the basis of age, sex, and geographical area, we analyzed their responses to some of the questions that were asked during multiple rounds of the face-to-face panel-recruiting interviews. Using Cohen's d for survey items that could be analyzed numerically and Cramér's V for categorical items, we were able to conclude that the respondents to the 2020 surveys were equivalent to the non-respondents in terms of both demographics and in the answers they originally gave to substantive questions on a variety of topics related to social science or public opinion research, including questions about quality of life, societal issue, and politics (Cohen's d items <0.2, 95% CI; Cramér's V items <0.1, 95% CI). This analysis may provide a model for others who wish to test the continued representativeness of their panel or who would like to use a different survey mode or change some other aspect of their methodology and test whether it is equivalent to their former methodology. Our success in building a panel that retained its representativeness may be useful to those in other countries where face-to-face surveys had previously been the norm but are becoming increasingly difficult to conduct.

• Asian Journal for Public Opinion Research
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• v.11 no.3
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• pp.257-273
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• 2023

Conducting face-to-face surveys is difficult and cost prohibitive, necessitating a new attempt to build a probability-based panel in South Korea. Since 99.9% of adult Koreans own a mobile phone, mobile phone numbers provide a viable sampling frame. Random digit dialing (RDD) surveys were conducted August-December 2021. Of the 288,056 valid phone numbers dialed, 13,655 respondents between the ages of 19 and 69 completed a phone survey. These respondents were later invited by text message to join a panel; 3,202 of these (23.4% or 1.2% based on the number initially contacted) joined the panel. When compared to official government statistics like resident registration data, the census, or the Social Survey, this new probability-based panel can be said to be representative of the Korean population on the basis of age, gender, location, marital status, and household size after weighting is applied. However, even after weighting, panel members are more educated than the general population, white-collar workers and self-employed people are overrepresented, and blue-collar workers are underrepresented. As of February 2023, this panel has grown to 10,471 participants with plans to continue to invite more panel members in the same way. Based on the comparisons in this paper, we can regard this panel as a cost-effective, probability-based panel that may be used for various kinds of public opinion research, by researchers both within and outside of Korea. As we continue to refine and grow this panel, we hope it will become more widely used by researchers as well as provide a model for those building similar panels in other countries.

• The Journal of Information Systems
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• v.32 no.3
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• pp.151-164
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• 2023

Purpose This study aims to analyze the current status of consumer awareness on Internet banks by conducting a full investigation and collecting user opinions presented on Google Play. After cateogorizing the current dissatisfaction, we would like to present not only the direction of the Internet bank service of but also the improvements of the platform. Design/methodology/approach Using opinion mining, subjectivity analysis, polarity analysis, and polarity information analysis of comments were conducted step by step to extract negative and positive keywords. The extracted keywords analyzed the weights of the frequently appearing positive and negative keywords using the TF-IDF model. Based on previous studies that negative information is more sensitive to positive information, we tried to confirm the connection, proximity, and mediation of negative keywords. Semantic Network Analysis (SNA) was used to visualize the connection relationship between the negative comment keywords of the three Internet banks. Findings Domestic Internet banks such as Kakao Bank, K-Bank, and Toss Bank have attracted a lot of attention even before they were established, and after establishment, they have secured a wide range of users through platforms that are completely different from existing banks. This study found out that the convenience of the app affects the opening and transaction of non-face-to-face accounts, which are characteristics of domestic Internet banks, which also affects the bank's business strategy. In addition, this study shows that the business characteristics of the company can be identified.

• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.48-62
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• 2016

Consumers have come to demand high quality, affordable prices, and innovative product designs of the outdoor wear market due to their well-being and leisure oriented lifestyle. A new system of business in outdoor wear has emerged in the process through which corporations have endeavored to satisfy such consumer needs. Outdoor wear brands have utilized social network services (SNS) such as Facebook and Twitter as means of marketing and have built close relations with consumers based on communication through these media. Recently, explosively escalating SNS data are referred to as social big data, and now that every consumer online is a commentator, reviewer, and publisher, the outdoor wear market and all of its brands have to stop talking and start listening to how they are perceived. Therefore, this study employs Social $Metrics^{TM}$, a social big data analysis solution by Daumsoft, Inc., to verify changes in the allusions related to outdoor wear market found on SNS. This study aims to identify changes in consumer perceptions of outdoor wear based on changes in outdoor wear search words and trends in positive and negative public opinion found in SNS social big data. In addition, products of interest, the major brands mentioned, the attributes taken into consideration during purchases of products, and consumers' psychology were categorized and analyzed by means of keywords related to outdoor wear brands found on SNS. The results of this study will provide fundamental resources for outdoor wear brands' market entry and brand strategy implementation in the future.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.309-318
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• 2017

This study is for analyzing the tone, the frame and the characteristics of political news in social media. Social news media is not same as old media in sharing news freely by SNS like tweeter, facebook and reporting, editing by anyone using SNS with various opinions. With Content analysis, sampling 419 cases from 'Wikitree' by the keyword, 'presidential election', all the full text analysed each how is social media making public opinion differently and which frame is using in. As the result, the social media has different tone, frame, and characteristic due to the reported figure, type of report, information source, attitude to the government, specifically shows a lack of in-depth report and distinct soft-journalism just same as old media's. Because the tone of social news media is not probable, specific but improbable, vague, using the irrational, strategic and episodic frame mainly.