• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.1-18
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• 2016

Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• Journal of Oral Medicine and Pain
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• v.31 no.4
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• pp.297-316
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• 2006

The increasing tendency of medical disputes is one of the remarkable social phenomena. Especially we must not overlook the phenomenon that production and circulation of information related to medical accidents is increasing rapidly through the internet. In this research, we evaluated the web sites which provide the information related to medical accidents using the keyword "medical accidents" in March 2006, and classified the 28 web sites according to the kinds of establishers. We also analyzed the contents of the sites, and checked and compared the current status of the web sites and problems that have to be improved. Finally, we suggested the possible solutions to prevent medical accidents. The detailed results were listed below. 1. Medical practitioners, general public, and lawyers were all familiar with and prefer the term "medical accidents" mainly. 2. In the number of sites searched by the keyword "medical accidents", lawyer had the most sites and medical practitioners had the least ones. 3. Many sites by general public and lawyers had their own medical record analysts but there was little professional analysts for dentistry. 4. General public were more interested in the prevention of medical accidents but the lawyers were more interested in the process after medical accidents. The sites by medical practitioners dealt with the least remedies of medical accidents, compared with other sites. 5. General public wanted the third party such as government intervention into the disputes including the medical dispute arbitration law or/and the establishment of independent medical dispute judgment institution. 6. In the comparison among the establishers of web sites, medical practitioners dealt with the least examples of medical accidents. 7. The suggestion of cases in counseling articles related to dental accidents were considered less importantly than the reality. 8. Whereas there were many articles about domestic cases related to the bloody dental treatment, in the open counseling articles the number of dental treatment regarding to non insurance treatment was large. 9. In comparing offered information of medical accidents based on the establishers, general public offered vocabularies, lawyers offered related laws and medical practitioners offered medical knowledge relatively. 10. They all cited the news pressed by the media to offer the current status of domestic medical accidents. Especially among the web sites by general public, NGOs provided the plentiful statistical data related to medical accidents. 11. The web sites that collect the medical accidents were only two. As a result of our research, we found out that, in the flood of information, medical disputes can be occurred by the wrong information from third party, and the medical practitioners have the most passive attitudes on the medical accidents. Thus, it is crucial to have the mutual interchange and exchange of information between lawyer, patients and medical practitioners, so that based on clear mutual comprehension we can solve the accidents and disputes more positively and actively.

• Korean journal of communication and information
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• v.26
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• pp.45-82
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• 2004

The purpose of this study is to examine the concept of civic journalism and the contents of Korean Internet newspapers that might reflect the possibilities of this new medium for civic journalism practices. This study examined how far and deep civic journalism practices have extended into Korean Internet newspapers as journalism's new tradition. More specifically, this study analyzed news articles of Korean Internet newspapers to uncover any differences among civic journalism Internet newspapers with different citizen reporter systems. The composite measure based upon ten elements of civic journalism practices was used as indicator of civic journalism practices. To obtain systematic data on news offered by Korean Internet newspapers on the World Wide Web, four major Internet newspapers, including Ohmynews, Ngotimes, Netpinion and Pressian were examined by a content analysis in April and May of 2003. Findings of this study reveal that many Korean newspapers do not fully exploit the opportunities and advantages offered by the new medium for civic journalism practices in online environments. Both aggregate and individual level of analysis for the civic journalism index reveal that there are some differences between non-civic journalism and civic journalism Internet newspapers using citizen reporter systems. However, overall performances of civic journalism Internet newspapers are not good enough to support the argument that civic journalism is well practiced in Korean Internet newspapers. Nonetheless, it would not be fair to conclude that Korean Internet newspapers have totally ignored the Internet's potential to increase the civic journalism performance in online environments.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.131-138
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• 2015

One of the most conspicuous characteristics of a business model that pursues expanding customer relationship is that it tries to lock in customers by encouraging them to repeat purchase in the long-term with the help of "Follow" function in Social Networking Service (SNS), which enables producers to automatically register the customers as potentially important ones and to offer them customized marketing services. In the value chain of the agriculture sector, producers of agricultural products can use SNS functions to provide loyal customers with valuable information and experiences such as the real-time information of their farm and products, hidden stories about the whole process from seeding to harvesting, and the storage and cooking methods of their products. These activities help the producers invoke customers' desire to live in the farm and to grow the products themselves. They also raise the accessibility of the producers' websites as customers are able to share a variety of news and knowledge such as the release of new products. This means that the producers's websites are now functioning to enable the producers to perform sales and promotion related activities. It is a big leap from the traditional e-commerce business model where sales and promotion of a product were separated and could be connected only through outside links. This two-way, viral characteristics of marketing services using SNS facilitate customers to share product information and their purchase experience with each other, which leads to more effective and efficient communication within the customer community.

• The Journal of Korean Obstetrics and Gynecology
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• v.19 no.1
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• pp.219-235
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• 2006

Purpose : To investigate the medical information related to HRT online and the medical treatment of perimenopausal and postmenopausal women in the Dept. of Ob&Gy Korean Medicine Hospital, after the discontinuance of the WHI trial in U.S, July 2002. Methods : With the key-words "HRT", "Hormone Replacement therapy", "호르몬 대체요법(HRT)", 갱년기 증후군(perimenopausal syndrome)", “폐경기후증후군(postmenopausal syndrome)", I searched for the information from July 2002 to 2005 on DAUM, the representative portal site in Korea, and I've got a grasp of the tendency of the informational propagation on HRT. Moreover, I investigated chief complaints and tendency of give up HRT of the perimenopausal and postmenopausal women(aged between 47 and 60) who visited Dept. of Ob&Gy Korean Medicine Hospital for 2 years and 6 months since July 2002. Results : 1) Searching for the news on DAUM, I found; 2 articles on the methods of HRT: 4 on the positive effects of HRT: 4 on the general items including the positive effects of HRT: 19 on the side effects of HRT: 1 on the insignificant effect of HRT :4 on the apprehensions about HRT: 3 on the strengthening of the criteria on medical fees review: 3 on the discontinuance of HRT: 8 on the alternative materials and medicines to HRT: 4 on the guidance for the phyto-estrogen. 2) I analyzed chief complaints of 120 women. The majority of chief complaints were vasomotor symptoms like hot flush and sweating. There were only 4 patients who wanted to give up HRT. Conclusion : The side effects of HRT were objectively dealt with online but there was not enough effective and continuous guidance. In the case that a woman not on HRT wishes to overcome perimenopausal period through KM therapy, this information may have affected her decision. However, not many women who were already on HRT terminated the therapy for fear of side effects and switched to KM therapy. Promotion of KM therapy in improving health during perimenopausal and postmenopausal period is desperately needed.

• Journal of the Korean Society of Food Culture
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• v.22 no.4
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• pp.492-497
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• 2007

The objectives of this study are to determine the full extent of the negative media reports and to broaden public awareness through content analysis. Samples of this study are news reports on vibrio on three major broadcasting companies such as MBC, KBS and SBS and three major national newspapers such as Chosun daily, Joongang daily and Donga daily in Korea for 5 years from January 1st in 2000 to December 31st in 2004. Total 628 cases were searched through from the web sites of fore mentioned TV and newspaper companies. It is highly advised to adhere to the proven fact as much as possible and full and thorough research on the outcome should be sought by media before they reach to the public.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.19-29
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• 2011

A Blog provides commentary, news, or content on a particular subject. The important part of many blogs is interactive format. Sometimes, there is a heated debate on a topic and any article becomes a political or sociological issue. In this paper, we proposed a method to predict the popularity of an article in advance. First, we used hit count as a factor to predict the popularity of an article. We defined the saturation point and derived a model to predict the hit count of the saturation point by a correlation coefficient of the early hit count and hit count of the saturation point. Finally, we predicted the virtual temperature of an article using 4 types(explosive, hot, warm, cold). We can predict the virtual temperature of Internet discussion articles using the hit count of the saturation point with more than 70% accuracy, exploiting only the first 30 minutes' hit count. In the hot, warm, and cold categories, we can predict more than 86% accuracy from 30 minutes' hit count and more than 90% accuracy from 70 minutes' hit count.

• Korean Journal of Health Education and Promotion
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• v.20 no.4
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• pp.95-109
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• 2003

Tobacco use is the most readily preventable cause of premature death； it is a worldwide problem, with a significant impact on heath and well-being. In order to design an effective tobacco education program, it is important to understand smoking patterns and the underlying factors associated with smoking in different generations such as adults or young people. Despite a general decline in the prevalence of regular smoking among adults, recent surveys commissioned by the Ministry Heath ＆ Welfare for the Republic of Korea have shown no evidence of any decline in smoking rates among young women and adolescents. The Republic of Korea has the highest adult male smoking percentage (65.1%) in the world and smoking in adolescents is still an increasing trend. Smoking in adolescents and young women is especially more dangerous, thus health education of anti-smoking directed at these groups is an important area that will benefit from using internet content that they can easily access. The purpose of this study is the evaluation of visual perception and effectiveness analysis in smoking cessation websites in promoting smoking cessation in adolescents and young women through Internet content. As a result of this project, at first we evaluated the Internet content of cyber smoking cessation programs by the evaluation criteria of web design interface. The Internet site of http：//nosmokeguide.or.kr received the most superior evaluation in the domestic Internet content for smoking cessation and the Internet site of the National Center for Tobacco-Free Kids received the most superior evaluation in the foreign Internet content for smoking cessation. This evaluation was surveyed by an expert in Internet content and user. Secondly, we developed the Internet content for cyber smoking cessation program, namely, "Dr. Smoking" that contained several menus and a database regarding anti-smoking designed in accordance with the results of this evaluation. The domain address of Dr. Smoking is http：//www.dmosmoking.com and our webpage has assorted kinds of news, information, self-diagnosis, prescription, consulting, a no-smoking mall etc. In conclusion, this project is designed to develop Internet content for the most effective smoking cessation program and to contribute to eliminating smoking from our society. We also will try to develop and upgrade this web-site in order to help a smoker who want to quit smoking and diminish the physical and socioeconomic harm from smoking.m smoking.