• The Journal of the Korea Contents Association
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• v.18 no.6
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• pp.217-234
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• 2018

In this study, big data analysis was conducted for domestic and international sports goods brands. Text Mining, TF-IDF, Opinion Mining, interestity graph were conducted through the social matrix program Textom and the fashion data analysis platform MISP. In order to examine the recent recognition of sports brands, the period of study is limited to 1 year from January 1, 2017 to December 31, 2017. As a result of analysis, first, we could confirm the products representing each brand. Second, I could confirm the marketing that represents each brand. Third, the common words extracted from each brand were identified. Fourth, the emotions of positive and negative of each brand were confirmed.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.149-156
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• 2021

Text mining is one of the useful tools to discover public opinion and perception regarding political issues from big data. It is very common that users of social media express their opinion with newly-coined words such as slang and emoji. However, those new words are not effectively captured by traditional text mining methods that process text data using a language dictionary. In this study, we propose effective methods to extract newly-coined words that connote the political stance and opinion of users. With various text mining techniques, I attempt to discover the context and the political meaning of the new words.

• Asian Journal for Public Opinion Research
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• v.12 no.2
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• pp.122-141
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• 2024

Drawing on mere exposure effect, we proposed that more exposure to a city, as measured by the number of channels of exposure, would increase familiarity, city image, and intention to visit that city. We conducted a survey of university students in seven Asian countries, asking them about a total of 14 cities, at least one from each of the surveyed countries. Exposure was found to be a significant antecedent and was most powerful when mediated by familiarity. Some types of exposure were stronger than others. Personal exposure, in the form of having visited a city or knowing someone who has, was the strongest type of exposure, with more than double the effect of media exposure. Social media, which is difficult to classify as either personal or media, was assessed separately and had a much smaller effect. The mere exposure effect exists whether the intention to visit a city is related to pleasure (tourism) or business.

• Journal of the Korea Fashion and Costume Design Association
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• v.26 no.2
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• pp.87-99
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• 2024

Freediving, an underwater leisure sport that involves diving without the use of a breathing apparatus, has gained popularity among younger demographics through the viral spread of images and videos on social media platforms. This study employs prominent Big Data analysis techniques, including text mining, Latent Dirichlet Allocation (LDA) topic analysis, and opinion mining to explore the keywords associated with freediving suits over the past five years. The research aims to analyze the rapidly evolving market trends of freediving suits and the increasingly complex and diverse consumer perceptions to provide foundational data for activating the freediving suit market and developing strategies for sustained growth. The study identified the keyword 'size' related to freediving suits and conducted opinion mining on 'freediving suit sizes'. Although the results showed a higher positive than negative sentiment, negative keywords were also extracted, indicating the need to understand and mitigate the negative factors associated with 'size'. The findings offer vital guidelines for the advancement of the freediving suit market and enhancing consumer satisfaction. This study is important as it contributes foundational data for continuous growth strategies of the freediving suit market.

• Journal of the Korean Institute of Rural Architecture
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• v.8 no.2
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• pp.19-26
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• 2006

This study is purposed to a ripple effects of development of a golf course in rural area analyzed to site suitability, social impact of public opinions, and economical impact. And for study, it is setting up development model of gamaksan golf course in geochang-gun will be constructed. It is carried out those as follows;(1) it is, first of all, examined site suitability considering act and site factors, opinion of residence's, and development planning of geochang-gun;(2) it is, secondly, suggested to analyzed social-economic impacts in rual area;(3) it is, finally, established an alternative proposal for development of a golf course considering it's merits and faults. The result of study, A appropriateness of development planning in golf course is focused to 'regional planning integrated', 'educational program for It's', and 'development council committee' considering harmony of a specialist, residents, government employee, businessman for a identity of interests.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.51-66
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• 2018

As AI (Artificial Intelligence) technologies have been swiftly evolved, a lot of products and services are under development in various fields for better users' experience. On this technology advance, negative effects of AI technologies also have been discussed actively while there exists positive expectation on them at the same time. For instance, many social issues such as trolley dilemma and system security issues are being debated, whereas autonomous vehicles based on artificial intelligence have had attention in terms of stability increase. Therefore, it needs to check and analyse major social issues on artificial intelligence for their development and societal acceptance. In this paper, multi-categorical sentiment analysis is conducted over online public opinion on artificial intelligence after identifying the trending topics related to artificial intelligence for two years from January 2016 to December 2017, which include the event, match between Lee Sedol and AlphaGo. Using the largest web portal in South Korea, online news, news headlines and news comments were crawled. Considering the importance of trending topics, online public opinion was analysed into seven multiple sentimental categories comprised of anger, dislike, fear, happiness, neutrality, sadness, and surprise by topics, not only two simple positive or negative sentiment. As a result, it was found that the top sentiment is "happiness" in most events and yet sentiments on each keyword are different. In addition, when the research period was divided into four periods, the first half of 2016, the second half of the year, the first half of 2017, and the second half of the year, it is confirmed that the sentiment of 'anger' decreases as goes by time. Based on the results of this analysis, it is possible to grasp various topics and trends currently discussed on artificial intelligence, and it can be used to prepare countermeasures. We hope that we can improve to measure public opinion more precisely in the future by integrating empathy level of news comments.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.109-121
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• 2015

The purpose of this qualitative study is to explore consumer behavioral trends, psychological characteristics and various cognitive types of Millennial Generation consumers, primarily in their 20s, who are familiar with sharing economy services based on the emerging social networking technology. Using Q methodology, this paper theoretically defines four and interprets via a social science perspective four different types of these young consumers who are skilled at state-of-the-art ICT equipment, devices or online networking services. Sharing economy services in Korea's academic and industrial services are influenced by government policy, and related research is relatively new. This study is focused on discovering unique psychographic characteristics called 'schemata' that include personal interest, preference, attitude, and opinion. On the basis of 40 Q-sorted data samples, the analysis examined 180 collected statements from meta-studies and interviews with 35 individuals born between 1997 and 1992. As a result, four consumer groups were identifies: Type 1 'Early majority', Type 2 'Laggard', Type 3 'Opinion leader', and Type 4 'Late majority'. The results of this research can be used to explore to study in greater detail the behavior and psychological aspects of Millennial General consumers'.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.37-46
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• 2017

Recently, disaster caused by social factors is frequently occurring in Korea. Prediction about what crisis could happen is difficult, raising the citizen's concern. In this study, we developed a program to acquire tweet data by applying Python language based Tweepy plug-in, regarding social disasters such as 'Nonspecific motive crimes' and 'Oxy' products. These data were used to evaluate psychological trauma and anxiety of citizens through the text clustering analysis and the opinion mining analysis of the R Studio program after natural language processing. In the analysis of the 'Oxy' case, the accident of Sewol ferry, the continual sale of Oxy products of the Oxy had the highest similarity and 'Nonspecific motive crimes', the coping measures of the government against unexpected incidents such as the 'incident' of the screen door, the accident of Sewol ferry and 'Nonspecific motive crime' due to misogyny in Busan, had the highest similarity. In addition, the average index of the Citizens sentiment score in Nonspecific motive crimes was more negative than that in the Oxy case by 11.61%p. Therefore, it is expected that the findings will be utilized to predict the mental health of citizens to prevent future accidents.

• Journal of the Korea Safety Management & Science
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• v.10 no.2
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• pp.225-235
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• 2008

It is expected that the change of industrial structure of Knowledge based economy, and service based economy would affect on economic life of physically-challenged person with no exceptions. There have been some former studies which have been misunderstood the employment of disabled due to the declining employment of the disabled and prejudice to the disabled based on biased perspective and public opinion. This study have analyzed the employment conditions of the ordinary workers and disabled workers out of those prejudices and biased opinions. Wage, economic activity ratio, age, educational background and industry those 5 parameters are brought for analyzing the two comparison group. Each parameter have compared based on the statistical data of ordinary workers and disabled workers for past 7 years. Weight between each parameter have been drawn by collecting the experts' opinion using AHP(Analytic Hierarchy Process), and utility of employment of two comparison groups have been estimated through progress inclination of each parameter. Through the estimated outcome, present condition and controversial issues and way of improvement of domestic employment of ordinary workers and the disabled is mentioned.

• Asian Journal for Public Opinion Research
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• v.3 no.1
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• pp.40-62
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• 2015

The main objective of this study was to investigate the awareness and perception of young professionals in Malaysia, Indonesia, and Vietnam countries on the ASEAN Economic Community (hereafter, AEC). Data from a survey of 575 young professionals, with approximately equal distribution from each country, were collected in June and July 2015. Research findings revealed that the knowledge and understanding of the AEC among the Gen Y professionals were still marginal. Although they lack awareness, young professionals had a good impression and perception of the AEC in connection with important benefits for them individually as well as for their country. Finally, the study revealed that the Gen Y professionals showed some level of optimistic attitude that they could succeed in the AEC as they thought that they were quite well prepared, having sufficient skills to work or to do business in other ASEAN countries.