• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.453-462
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• 2016

Since the Internet provides a way of expressing and sharing Internet users' mindsets, corporate marketers want to acquire measurable and actionable insights from web data. In the past, companies used to analyze the attitude, satisfaction, and loyalty of consumers toward their brands using survey data, whereas nowadays this is done using the big data extracted from Social Network Services. In this study, we propose a framework for clustering brand names using the social metrics gathered on social media. We also conduct a case study of the automobile industry to verify the feasibility of the proposed framework. We calculate the brand name distance for each pair of brand names based on the total number of times that they are mentioned together. These distances are used to project the brand name onto a 3-dimensional space using multidimensional scaling. After the projection, we found the clusters of brand names and identified the characteristics of each cluster. Furthermore, we concluded this paper with a discussion of the limitations and future directions of this research.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.367-376
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• 2020

According to recent statistics on new consumer market trends, 'alone consumption' is at the center. This study focuses on the social big data that attracts the public's opinions in that it is important for a certain social trend to comprehensively understand the various fields such as society, locality, culture, marketing, economics, and psychology that form the background for it. Therefore, we set up the linkage of 'solo consumption' and conducted research on new consumer market trends using Opinion Analisys. As a result of this trend analysis, representative keywords such as 'honbab', 'honsul' and 'honyoeng' were derived and analyzed the trend of new consumer market using this data. Alone consumption is an inevitable new consumption trend caused by demographic change after the global economic crisis. The importance as a trend reflecting this will be further strengthened. Trend analysis by social big data will help scientific and systematic business distribution strategies and planning to help make new and valuable decisions and decisions about new consumer markets.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1207-1219
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• 2014

In this study, 1) we compare face channel and non-face channel of life insurance company and non-life insurance company with insurance employs' suitability opinion about channel type, channel property, channel evaluation items requiring when selling insurance products, 2) we construct two social networks for life insurance companies and non-life insurance companies and find/compare two networks' properties, and then want to suggest any direction about sale channel strategy. As the result of comparing social networks of life insurance company and non-life insurance company created by insurance selling channel fit evaluation, employs of life insurance companies have more common opinion than those of non-life insurance companies and so can have more same directional channel strategy. However, property insurance companies need to manage their own channel strategy based on their own circumstance.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.133-140
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• 2020

Emotional analysis is an application of opinion mining that analyzes opinions and tendencies of people appearing in unstructured text. Recently, emotional analysis of social media has attracted attention, but social media contains newly-created words and slang, so it is not easy to analyze with existing emotional analysis. In this study, I design a new emotional analysis system to solve these problems. The proposed system is possible to analyze various emotions as well as positive and negative in social media including newly-created words and slang. First, I collect newly-created words and slang related to emotions that appear in social media. Then, expand the existing emotional model and use it to quantify the degree of sentiment in emotional words. Also, a new sentiment dictionary is constructed by reflecting the degree of sentiment. Finally, I design an emotional analysis system that applies an sentiment dictionary that includes newly-created words and an extended emotional model.

• 한국정보교육학회:학술대회논문집
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• 2011.01a
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• pp.233-240
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• 2011

Social Media is the open online tool and media platform for sharing and participation of users opinion, experience, viewpoiont, so general situation that is one-side flowing from production to consume doesn't act, and while use of two-way, user create contents use of sharing and participation. This social media include Blog, Social Network Service(SNS), Wiki, User Create Contents(UCC), Micro Blog, 5 types. In broad terms, Social Learning is self-learning that user sharing with coperation and collective intelligence through Social Media, and in few wards Social Learning is learning for Social Media. In this research, we define Social Media and Social Learning, and research of method of use of Elementary Education.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.329-340
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• 2015

In the age of media convergence, this study intended to empirically examine the influences of entertainment programs on the formation of public opinion in Twitter using the case of the Healing Camp, an entertainment program of SBS, featured Cheol Soo Ahn, who was a presidential candidate. Through a content analysis this study was able to directly test how public opinion was developed in Twitter and also examine the dynamics in which the messages of traditional media influence the formation of public opinion in twitter by combining Twitter and actual contents of the TV program. The study is expected to contribute to expanding a scope of scholarly attention of social media.

• Asian Journal for Public Opinion Research
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• v.4 no.4
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• pp.208-245
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• 2017

Background: Attitudes toward breastfeeding in public are one potential barrier to optimal breastfeeding rates and durations. Method: Questions about breastfeeding experience and attitudes toward breastfeeding in public were asked in face-to-face interviews as part of the Korean Academic Multimode Open Survey (KAMOS), May-July, 2017. The response rate was 65.8% (2000 respondents nationwide). Results: A majority of Koreans disagreed (1 or 2 on a 4-point scale) with the statement "Women should not breastfeed their child in open, public places" (53.9%) and agreed (3 or 4 on the 4-part Likert scale) with the statements "I do not feel uncomfortable seeing women breastfeed their child in open, public places" (64.0%) and "Breastfeeding a baby, instead of letting the baby cry, in public places is better for other people" (71.8%). However, despite these generally positive attitudes, the majority also said that they would not breastfeed in public (57.4% of women) or, in the case of men, would not want a close female relative to do so (63.8% of men). Breastfeeding in public was positively correlated with the duration of breastfeeding. People were more positive about breastfeeding in public if they: were parents; did not use formula and breastfeeding a similar amount; had children who had been breastfed in public; were older; were Buddhists rather than Christians. An attempt was made to compare attitudes toward breastfeeding in public and breastfeeding durations internationally, but was inconclusive due to not perfectly comparable data. Conclusion: Our results may be useful in planning public health campaigns in South Korea or future attempts at international comparisons to better understand and address the effect of public opinion regarding breastfeeding in public on breastfeeding rates and durations.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.2
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• pp.189-200
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• 2019

Korean seafarers have played a key role throughout the country's history and economic development. They have been a major source of foreign remittance into the nation as well as a pivotal sector in emergency logistics during war times. However, the current number of Korean seafarers in decreasing due to low job attractiveness and retention rate onboard. This is a major problem for the national and international shipping industry as youth seem not to be interested in working onboard for long periods of time. The purpose of this study is to 1) determine what the public opinion about seafarers in Korea is and 2) find out what factors mostly stand out in the public opinion about seafarers profession. The paper suggests that three main types of opinion groups emerged. The first type is labeled as 'high risk, high workload and high stress' as respondents recognized a high possibility of accident onboard and, at the same time, acknowledged that seafarers can be fatigued and stressed. The second type was named as 'Dangerous, Dirty, Difficult', as seafarers' image was mainly associated to fishing vessels and not to merchant and passenger ships. The third type recognized that the social position of the seafarers was low due to 'low social recognition'. The study suggests that all three types have a negative image of seafarers' job. Based on the results of this study, it is necessary to establish various policies and marketing tools to improve the negative job image linked to seafarers by the public opinion. If the public image of seafarers can be improved and attractiveness rose, it is expected a higher number of seafarers will pursue and keep a career at sea.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.173-187
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• 2012

As newspapers which have been major news media are being replaced by on-line news media in recent years, many researchers are paying attention to "comments(news users' short remarks on an article)", a newly emerged way of forming public opinion. This study is examining how the similarity between political disposition of on-line news visitors and that of news media impacts upon their evaluation on quality of comments from the viewpoint of 'social identity theory.' This study may have academic significance because it inspected the pattern of media usage and the cognition of comments in relation to political disposition for the first time and showed 'comments reading' and the function of comments to form public opinion(comments journalism).

• KIISE Transactions on Computing Practices
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• v.20 no.9
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• pp.492-497
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• 2014

In this paper, we propose a method of retrieving opinioned tweets in Twitter, which is the one of the popular Social Network Services and shares diverse opinions among various users. In typical opinion retrieval systems, they may consider the presence of sentiment phrases (subjectivity) as the important factor even if the subjective phrases are not related to a given query or speaker. To alleviate these problems, we utilized the syntactic structure of a sentence to identify the relationships between 1) subjectivity-query and 2) subjectivity-speaker and 3) the syntactic role of subjectivity. Besides, our learning-to-rank approach is trained to retrieve opinioned tweets based on query-relevance, textual features, user information, and Twitter-specific features. Experimental results on real world data show that our proposed method can achieve better performance than several baseline methods in terms of precision and nDCG.