• Journal of the Korean Society for information Management
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• v.27 no.1
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• pp.7-24
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• 2010

This study tried to develop the confidence indicators and evaluation factors of credibility according to the types of online information by nationwide large scale online survey. The main results are summarized as follows: i) confidence indicators by types of online information: information on news sites(72.553), financial companies(68.894), government sites(67.938), cafe(66.464), portal sites(65.001), collective intelligence sites(63.489), nonprofit organization (63.392), company/corporation sites(59.789), blog(59.066), online community sites(55.609), e-commerce sites(55.118), mini-homepage(50.695). ii) 'Widely known site' or 'famous site' is the most important factor for all types of online information. User opinions like as posting or comment are major factors for sites of cafe, blog, mini-homepage, online community, collective intelligence etc. and 'name recognition' and 'reputation' are main factors for site of financial company, corporation, government, nonprofit organization.

• The Journal of Korean Association of Computer Education
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• v.7 no.3
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• pp.67-78
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• 2004

Since the 7th National Curriculum was established, ICT has emerged as an indispensable tool for teaching a variety of subjects in K-12 education systems. This paper develops the model for explaining the factors affecting students' satisfaction level in using web contents for science class. Based on data collected from a questionnaire survey from the students who evaluated the web sites providing the information related to the science subject, the structural equation model is presented. From this model, a following conclusion is provided : credibility and understandability/motivation are the most important factors affecting the level of satisfaction, but the presentation method, the screen design as well as contents itself has indirect impact on user satisfaction through understandability/motivation. Other interesting results are also provided. This result might provide the useful guidelines for designing the web-contents for science class in high school.

• Korean Journal of Community Nutrition
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• v.8 no.3
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• pp.259-269
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• 2003

The purpose of this study was to develop a nutrition education website for children, especially those around the 4th-6th grade levels. Among the already existing websites providing nutritional information for children, 7 websites with comparable amounts of information were evaluated in terms of their topics, credibility, content, ease of use, and aesthetics. In addition, a survey was conducted to assess the need for nutrition information among 305 elementary students. The food pyramid was the topic offered most often on those websites. Information on nutrients, digestion, food safety, nutrition labeling, and healthy eating habits were available on the websites. Some of those websites also provided games or quizzes to attract the children's interest. However, seine of the websites did not give any information on the person responsible for providing the information, which is most important in determining the credibility of the website. Other problems were that some information was too difficult for children, and some of the websites did not provide a way to search for information. According to the survey results, the topics that children wanted to know about were‘desirable weight’,‘cooking’,‘correct food choice’,‘weight control method’,‘calories consumed during exercise’, but, they did not have a high interest in‘asking questions’‘books with nutrition messages’,‘under weight’,‘negative effect of weight control’and‘helping hungry children’. Based on these results, we developed a new nutrition education web-site, ifood’(http: //1 ifood.or.kr). We focused on helping children develop healthy eating habits by providing information which is easy and practical for children. However, we neither included the program to assess their dietary intake, nor provided entertaining background sounds, which children like. Also, the game section is composed mainly of quizzes. Therefore, we need to further develop exciting games to teach nutrition to children. In the near future, the newly developed website should be evaluated by children regarding understandability and coverage of the contents as well as usability and design, and then revised to improve the educational effect.

• Journal of Global Scholars of Marketing Science
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• v.9
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• pp.203-219
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• 2002

The purpose of the study is to analyze environmental changes in market, customer and information technology of Internet fashion industry, to present fashion company's current situation and strategy for confronting business environmental changes, and to propose the direction of the future research in this fashion field. First, the importance of Internet has been increased due to the rapid growth in number of Internet user and the size of the e-commerce. Second, to satisfy the customers requiring reasonable price and differentiated product and service, e-Branding strategy implementation, customized service development and enhancement on Web-site credibility and loyalty are demanding in the market. Third, development on the mobile technology and the increase in the Internet user using mobile communication device requires preparing mobile consuming environment, new business platform. Fashion industry's current situation and competitive strategy developed by the environmental change analysis were used for developing future research direction, that is, the m-business, CRM, and e-Branding. Through the understanding of environmental changes in Internet fashion industry and proposed research direction, research on Internet fashion marketing is hoped to be vitalized. Results of this study were expected to be utilized the strategy development.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.199-219
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• 2018

With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.