• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.24-44
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• 2014

This study explores the political meaning of candidate's speech and statement who run for the 18th presidential election in the viewpoint of communication. The visibility of the words and the connectivity between the words are analyzed in the viewpoint of structural aspect and the vision, policy. The visibility of the words is analyzed based on the frequency of the words mentioned in the speech or the statement. The connectivity between the words are analyzed based on the network analysis and expressed by graph. In the case of candidate Park, the key word is the happiness of the people and appointment. The key word for candidate Moon is regime change and the Korean Peninsula and the key word for candidate Ahn is the people and change. This study contributes positively to the study of candidate's discourse in the viewpoint of methodology by using network analysis and exploring scientifically the connectivity of the words. In the theoretical aspect this study uses the results of network analysis for revealing what is the leadership components in the speech and the statement. In conclusion, this study highlights the extension of the communication studies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.679-689
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• 2013

To relieve Green-house Gas Emission is the key issue in urban area. Urban transport policies have focused on the reduction of private car use. The most common of these is Travel Demand Management(e.g., congestion charge, environmental tax, etc.) that forces individuals to reduce their private car use. An alternative way is Mobility Management(MM) that induces individuals to voluntarily change their car use through communications. MM is founded on social psychology theory and focuses on individuals' decision making processes to change their perception and attitude on private car use. Although some researchers have reported the relevance of MM approach, still few researches have explicitly studied on individuals' decision making processes. Therefore, the aims of the paper are to analyze the decision making process of individuals and to provide the basis of introducing MM approach in Korea. Structural equation model(SEM) is applied for the analysis of individuals' decision making process. A empirical study shows that psychological factors such as perception/attitude on global environment or individual norms impact significantly to reduce private car use and accordingly the relevance of introducing MM approach instead of imposing regulations or expanding transport facilities.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.199-210
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• 2019

Virtual Advertising, which was introduced exclusively in sports casting programs in 2010, has enlarged its scope to terrestrial TV networks' sports news, entertainment shows, and dramas by 2015. Such advertising deregulation allows broadcasting business operators to insert more various virtual advertising methods into TV programs. Despite recent evaluation that virtual advertising was deregulated to a large degree, it is still inadequate compared to foreign state of affairs and has a lot of room for growth. Therefore, this research explores a literature review of virtual advertising in other countries and considers possible ways for virtual advertising in Korea to move forward. Additionally, through in-depth interview with seven virtual advertising experts, the research unravels positive and negative impacts of virtual advertising as well as its current state of affairs and struggles. This research also analyses the regulation of virtual advertising and finally explores possible revitalization strategies. The results of the research show that it is necessary to first improve the viewers' favorable concerning virtual advertising in order to revitalize virtual advertising. Revitalization will also require a clarification of regulation as well as a more unified and consistent content review and rating system. Furthermore, it is imperative that data of advertising impact will be accessible to advertisers and that advertising regulation will loosen. Revitalization will also require a clarification of regulation as well as a more unified and consistent content review and rating system. Furthermore, it is imperative that data of advertising impact will be accessible to advertisers and that advertising regulation will loosen. It is necessary to further develop new techniques and creators of virtual advertising. The research suggests strategies and alternative paths for the growth and revitalization of the virtual advertising market in light of recently revised law.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.299-307
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• 2014

Nowadays, SNS media has become one of the most common and economic communication methods in the modern word. With the rapid development of communication technology, a variety of SNS media makes easier for us to reach other people everywhere and people are getting more and more reliant on them. The surge in SNS media users and SNS media diversity gets more important every day, but academic research on SNS media evaluation program is scanty. In order to present an evaluation program on the SNS media, this study selected some applicable measurement factors based on reference research, and then evaluate major SNS medias by using AHP analysis method. With these purposes, Kakaotalk, Twitter and Facebook, are the three major SNS medias that were chosen for the analysis. Through collections and analysis of usability evaluation factors about SNS quality from related literature, some factors were concluded: system quality, information quality, interface quality and service quality, to build an AHP frame. And to achieve these purposes, this study applied comprehend mutual questionnaire survey for experts and users to gather research date. Empirical studies about the results were performed using AHP method with Microsoft Office Excel 2010. In this study, the final SNS media evaluation result is that Kakaotalk ranks first of the three SNS media, Facebook is in the second place, and Twitter as least. When SNS media are evaluated, system quality, information quality, interface quality and service quality should be considered. Among all factors, service quality is the most important.

• Archives of design research
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• v.17 no.3
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• pp.133-146
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• 2004

Diagrams have been deeply and widely used for supporting effective communication relating to design information and knowledge in most design fields. The results show that their role expands to "developmental design material" increasing the principle and method of design process. It's recent trend that Digital-Diagrams are aggressively used in multimedia design fields such as web contents, interactive movies and DVD Titles in order to support user's information understanding more effectively and to stimulate user's participation in information acquiring process. This study aims to clarify the essence of digital diagram corresponding to infographic material in multimedia design and application of multimedia contents development process . This study purpose leads to argue the substance of Digital-Diagrams as one of infographic types and identity of Digital-Diagrams which is relatively compared to existing Diagrams. Eventually, this study examines the application issues of Digital-Diagrams in multimedia design process. Regarding the identity of Digital-Diagrams, they are functionally utilized depending on hypertext based on language forms and interactivity based on graphical forms as core attributes. Therefore, they semantically enlarge user s information understanding by segmenting hierarchy of information expression and rather support user s acquisition of information control ability. Relating to multimedia design process, Digital-Diagrams are used by information designers and navigation designers as method for ‘modeling for realization based on information acquisition support for information-users. Especially, the study results show that the applications of Digital-Diagrams are performed for information representing methods for information designers and embodiment of useful functional factors of interface for navigation designersgation designers.

• The Journal of Information Systems
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• v.25 no.1
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• pp.1-23
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• 2016

Purpose Self-congruity deals with the effect of symbolic value-expressive attributes on consumer decision and behavior, which is the theoretical foundation of the "non-utilitarian destination positioning". Functional congruity refers to utilitarian evaluation of a product or service by consumers. In addition, recent years, social network services, especially mobile social network services have created many opportunities for e-WOM communication that enables consumers to share personal consumption related information anywhere at any time. Moreover, self-construal is a hot and popular topic that has been discussed in the field of modem psychology as well as in marketing area. This study aims to examine the moderating effect of self-construal on the relationship between self-congruity, functional congruity and tourists' positive electronic word of mouth (e-WOM). Design/methodology/approach In order to verify the hypotheses, we developed a questionnaire with 32 survey items. We measured all the items on a five-point Likert-type scale. We used Sojump.com to collect questionnaire and gathered 218 responses from whom have visited Korea before. After a pilot test, we analyzed the main survey data by using SPSS 20.0 and AMOS 18.0, and employed structural equation modeling to test the hypotheses. We first estimated the measurement model for its overall fit, reliability and validity through a confirmatory factor analysis and used common method bias test to make sure that whether measures are affected by common-method variance. Then we tested the hypotheses through the structural model and used regression analysis to measure moderating effect of self-construal. Findings The results reveal that the effect of self-congruity on tourists' positive e-WOM is stronger for tourists with an independent self-construal compared with those with interdependent self-construal. Moreover, it shows that the effect of functional congruity on tourists' positive e-WOM becomes salient when tourists' self-construal is primed to be interdependent rather than independent. We expect that the results of this study can provide important implications for academic and practical perspective.

• 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.