• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Asian Journal for Public Opinion Research
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• v.4 no.3
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• pp.123-165
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• 2017

In this paper, we look at mediation of public policies in different areas of governance. Editorials appearing in an Indian English language newspaper during the period of an intense public debate on the issue of affirmative action in favor of a section of the population, the Other Backward Classes (OBC) - a popular reference to the socially and educationally backward classes of citizens under India's constitution constitute the sample for the study. Apart from editorials on the public policy of reservation of seats in admission to higher education institutions for the OBC, editorials on three other areas of governance, namely, development, economy, and public administration appearing in the same newspaper, are also consulted to understand media framing of social issues and more specifically, issues of social justice. Inductively identifying the various frames used in its editorials by the newspaper, I detect predominant use of 'personalized' frame in respect of editorials pertaining to the policy area of social justice; and distinguish it from the 'generic' frame of 'characterization' found in theory. The study concludes that the sample editorials in respect of other public policies did not use the personalized frame found in editorials on social justice.

• Journal of Digital Contents Society
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• v.15 no.5
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• pp.621-630
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• 2014

The purpose of this study is to extract metaphor characteristics of Social Network Service. Social Network Service is different from existing media only available in one-way communication, each individual expands opinion by sharing daily life and opinion directly and interpreting another user's post. This Study premise that the reason of converting from passive reader to active enunciator is the metaphor characteristics of Social Network Service by 'Source Domain' and 'Target Domain'. In addition, this study examines the meaning of structure user's text production and interpreting based triple mimesis of Paul Ricoeur. This study has significance as arguing with existing study on SNS as metonymic media and suggesting metaphor characteristics and meaning of Social Network Service.

• Asian Journal for Public Opinion Research
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• v.9 no.1
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• pp.25-47
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• 2021

This study analyzes 419 fake news items published in India, a fake-news-prone country, to identify the major themes, content types, and sources of social media fake news. The results show that fake news shared on social media has six major themes: health, religion, politics, crime, entertainment, and miscellaneous; eight types of content: text, photo, audio, and video, text & photo, text & video, photo & video, and text & photo & video; and two main sources: online sources and the mainstream media. Health-related fake news is more common only during a health crisis, whereas fake news related to religion and politics seems more prevalent, emerging from online media. Text & photo and text & video have three-fourths of the total share of fake news, and most of them are from online media: online media is the main source of fake news on social media as well. On the other hand, mainstream media mostly produces political fake news. This study, presenting some novel findings that may help researchers to understand and policymakers to control fake news on social media, invites more academic investigations of religious and political fake news in India. Two important limitations of this study are related to the data source and data collection period, which may have an impact on the results.

• Asian Journal for Public Opinion Research
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• v.11 no.1
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• pp.4-30
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• 2023

Previous research has empirically demonstrated the negative effects of social media use on young people's psychological well-being. Unlike most previous studies that focused on either Facebook or Instagram, this study comparatively examined the differences in upward comparison and its effects on self-esteem, life satisfaction, and depression between Facebook and Instagram. An analysis of survey data from 641 Korean college students, who reportedly use these two social media more actively than any other age group, found that college students experience more upward comparisons on Instagram than on Facebook. Upward comparisons on both Facebook and Instagram increased by college students' age and weekly usage time. Upward comparisons on Instagram increased by the additional factors of gender (females more than males) and number of "followings." Subsequently, the effects of upward comparison on psychological well-being were found to differ by social media platform. Upward comparisons were found to negatively impact all determinants of psychological well-being only on Instagram, but not on Facebook. The differences in upward comparison and its impact on young users' psychological well-being found in this study were discussed in terms of the different functional characteristics of the two social media platforms, which provides direction for further research needed to establish guidelines for healthy social media use by young people.

• Journal of the Korean Society of Costume
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• v.58 no.2
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• pp.1-14
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• 2008

This study aimed to investigate the associations between clothing consumption values and the ambivalent clothing consuming behavior of young female adults. To explain the ambivalent consuming behavior prevailing in the contemporary fashion market, five dimensional consumption values proposed by Sheth(1991) were adopted as explanatory factors, and fashion leadership and spending were included as moderating factors. Data collecting using written survey instrument yielded one hundred and seventy two complete responses from female consumers aged between 20 and 39. Factor analysis on clothing consumption values resulted in five dimensional structures of consumption values for the sample: expressive, epistemic, functional, social, and fashionable values. Among these, expressive, functional, and social values significantly affected ambivalent consuming behavior. The effect of expressive value was strong regardless of fashion innovativeness, opinion-leadership, and monthly income of consumers, however, the effects of epistemic, functional, and social values were changed depending on the moderating factors.

• Asian Journal for Public Opinion Research
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• v.3 no.4
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• pp.156-175
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• 2016

This paper considers whether random sampling always produces more accurate survey results in the case of South Korea. We compare information from the 2010 census to the demographic variables of three public opinion surveys from South Korea: Gallup Korea's Omnibus Survey (Survey A) is conducted every two months by Gallup Korea; the annual Social Survey (Survey B) is conducted by Statistics Korea (KOSTAT); the Korean General Social Survey (KGSS or Survey C) is conducted annually by the Survey Research Center (SRC) at Sungkyunkwan University (SKKU). Survey A uses quota sampling after randomly selecting the neighborhood and initial addresses; Survey B uses random sampling, but allows replacements in some situations; Survey C uses simple random sampling. Data from more than one year was used for each survey. Our analysis suggests that Survey B is the most representative in most respects, and, in some respects, Survey A may be more representative than Survey C. Data from Survey C was the least stable in terms of representativeness by geographical area and age. Single-person households were underrepresented in both Surveys A and C, but the problem was more severe in Survey A. Four-person households and married persons were both over-represented in Survey A. Less educated people were under-represented in both Survey A and Survey C. There were differences in income level between Survey A and Survey C, but income data was not available for Survey B or the census, so it is difficult to ascertain which survey was more representative in this case.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.111-130
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• 2013

As the number of online social networking service (SNS) users is increasing, various efforts are being deployed to take advantage of SNS from the perspective of business and management. Especially, researches in the field of marketing such as word-of-mouth (WOM) effect have been actively conducted. This paper examined the impact of the SNS messages of users' friends on the users' attitude and the moderating effect of the friends' opinion leadership on the WOM effect. Fifty-one Facebook users responded to the questions on their four friends each. Regression analyses showed that there existed WOM effect under the SNS environment and the opinion leadership of the message creators positively moderated the WOM effect. We discussed the contributions and implications of this study.

• Korean Journal of Health Education and Promotion
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• v.28 no.2
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• pp.1-13
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• 2011

Objectives: This study investigated beliefs of Koreans on the usefulness of various resources they use to alleviate depressive symptoms and to identify factors affecting the beliefs on different approaches to depressive symptoms. Methods: A household survey was conducted on a stratified sample of adults of age 18~74 (N=1,607) in 2009. The participants were asked to read a case vignette of depression and to provide their opinion about usefulness of 39 types of resources as ways of addressing the symptoms. Factors affecting opinions on usefulness of various resources were examined with logistic regression. Results: The three approaches identified via factor analysis were believed to be useful in the order of 'psychological/relational/activity-oriented', 'lifestyle/cultural', and 'physical/medical' approaches. The logistic regression analyses revealed that correct recognition of symptoms increased the likelihood of positive opinion about psychological and physical approaches, and so did having current symptoms about physical and popular approaches. Past help-seeking experience increased the likelihood of negative opinion about physical approach, however. Conclusions: Strategies to adopt various types of resources need to be developed, including rigorous use of psychosocial methods, mechanisms to control service quality, and the integration of diverse resources into the current community mental health services.

• Information Systems Review
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• v.22 no.4
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• pp.59-74
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• 2020

This paper investigates the asymmetric effect of social sentimental on an individual stock price return. For this purpose, four companies such as POSCO, Korean Electricity, AMORE PACIFIC, KIA Motors are chosen from KOSPI listed companies in terms of dataperspective. The main estimation results are as follows: the positive opinions affect only the stock prices return of three companies while the negative opinions affect all of the companies. It shows that positive or negative texts give asymmetric effect on stock price return and the effect of negative opinions is bigger than that of positive opinions. The results imply that investors are more sensitive to the negatives since they have the tendency of loss aversion. Also, it indicates that subjective opinion on SNS can be used as the proxy for the investment sentiment.