• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.437-449
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• 2023

This study measured PM₁₀ concentrations and wind speeds in buffer green spaces and neighborhood parks located along the road, and compared them with roadside measurementresults to understand the effect of mitigating PM₁₀ concentrations by type of green space and the influence of wind speeds on it. As a result of the analysis, the effect of mitigating PM₁₀ concentration was different depending on the type of roadside green space, and an increase in wind speed had a significant effect on reducing PM₁₀ concentration. In buffer green areas with high planting density, wind speed was low and PM₁₀ stagnated inside, resulting in the highest concentration. On the other hand, green areas in neighborhood parks with relatively low planting density had high wind speeds and the lowest PM₁₀ concentration. The non-green area within the neighborhood park recorded the highest wind speed, which was advantageous for the spread of PM₁₀, but the concentration was higherthan that of the green area. Therefore, in orderto reduce PM₁₀ concentration in roadside green space, it is necessary to create green space with good ventilation, and the combined effect of green space and wind speed seems to be more advantageous in reducing PM₁₀ concentration. Green spaces capture and remove PM inside, contributing to reducing the concentration of PM outside. In order to manage PM in the entire city and on roads, it is necessary to increase planting density and leaf area in roadside green spaces, such as buffer green spaces, so that PM can be removed within the green spaces. However, in green spaces such as neighborhood parks that are actively used by city residents, in orderto minimize damage to users due to PM, it is desirable to create green spaces with a structure that allows PM to spread to the outside rather than stagnate inside.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.111-128
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• 2020

Recently, in the process of globalization of companies, the use of third party logistics providers (3PL) has been strengthened. Therefore, the purpose of this study is to test the effectiveness of the logistics information system provided by 3PL companies. This study is to test the relationship between the effect of the characteristics of the 3PL logistics information system on the shipper's supply chain performance, that is, logistics performance, customer performance, and organizational performance, and the shipper's loyalty to the 3PL company, that is, 3PL corporate performance. In addition, long-term relationship orientation is to test whether there is a moderating effect between the shipper company and the 3PL company. Through this, this study aims to provide strategic implications for improving the competitiveness of 3PL companies. In this study, a total 205 data were collected and used for analysis of shippers companies for hypothesis testing, and analyzed using SPSS 21.0 and AMOS 21.0 statistical programs. The results of the study are summarized as follows. First, it was found that the accuracy, timeliness, and usefulness of the 3PL logistics information system all had a significant positive (+) effect on the performance of the shipper's supply chain. Second, it was found that the accuracy, timeliness, and usefulness of the 3PL logistics information system all had a significant positive (+) effect on 3PL corporate performance. Third, it was found that the performance of the supply chain of the shipper company had a significant positive (+) effect on the performance of the 3PL company. Finally, it was found that long-term relationship orientation had a moderating effect on the relationship between the performance of the shipper company's supply chain and the performance of the 3PL company. The purpose of this study is to provide academic and practical implications for securing competitive advantage through the logistics information system of 3PL logistics companies.

• Food Science and Preservation
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• v.30 no.1
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• pp.109-121
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• 2023

This study was conducted to evaluate vitamin D intake of Koreans in a total diet study (TDS) and to determine the effect of irradiation on vitamin D synthesis in mushrooms. For analysis, sample were saponified and extracted with hexane, and vitamin D was quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Based on the validation results, the recovery of the National Institute of Standards and Technology (NIST) standard reference sample (SRM) 1849a was 96.7% and the z-score of -1.6 was obtained by the Food Analysis Performance Assessment Scheme (FAPAS) proficiency test (PT) 21115. Vitamin D₂ was not detected in any samples, and the highest level of vitamin D₃ was detected in mackerel and anchovies ranging from 24.2 to 120.2 ㎍/kg. The mean daily intake of vitamin D was 0.99 ㎍/day, as estimated from the vitamin D contents of the analyzed foods and their corresponding intake. The adequate intake (AI) of vitamin D based on the Dietary reference intakes for Koreans provided by the Ministry of Health and Welfare is 5-15 ㎍/day for Koreans aged 6 to 75 years. Compared with this AI, vitamin D intake of Koreans estimated in this study was inadequate. For that, the increased vitamin D content in ultraviolet (UV)/sun light irradiated mushrooms warrants further research to increase vitamin D intake of Koreans through diet.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• KDI Journal of Economic Policy
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• v.12 no.3
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• pp.27-45
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• 1990

Two opposing views prevail regarding the economic impact of rural out-migration on the rural areas of origin. The optimistic neoclassical view argues that rapid rural out-migration is not detrimental to the income and welfare of the rural areas of origin, whereas Lipton (1980) argues the opposite. We developed our own alternative model for rural to urban migration, appropriate for rapidly developing economies such as Korea's. This model, which adopts international trade theories of nontraded goods and Dutch Disease to rural to urban migration issues, argues that rural to urban migration is caused mainly by two factors: first, the unprofitability of farming, and second, the decrease in demand for rural nontraded goods and the increase in demand for urban nontraded goods. The unprofitability of farming is caused by the increase in rural wages, which is induced by increasing urban wages in booming urban manufacturing sectors, and by the fact that the cost increases in farming cannot be shifted to consumers, because farm prices are fixed worldwide and because the income demand elasticity for farm products is very low. The demand for nontraded goods decreases in rural and increases in urban areas because population density and income in urban areas increase sharply, while those in rural areas decrease sharply, due to rapid rural to urban migration. Given that the market structure for nontraded goods-namely, service sectors including educational and health facilities-is mostly in monopolistically competitive, and that the demand for nontraded goods comes only from local sources, the urban service sector enjoys economies of scale, and can thus offer services at cheaper prices and in greater variety, whereas the rural service sector cannot enjoy the advantages offered by scale economies. Our view concerning the economic impact of rural to urban migration on rural areas of origin agrees with Lipton's pessimistic view that rural out-migration is detrimental to the income and welfare of rural areas. However, our reasons for the reduction of rural income are different from those in Lipton's model. Lipton argued that rural income and welfare deteriorate mainly because of a shortage of human capital, younger workers and talent resulting from selective rural out-migration. Instead, we believe that rural income declines, first, because a rapid rural-urban migration creates a further shortage of farm labor supplies and increases rural wages, and thus reduces further the profitability of farming and, second, because a rapid rural-urban migration causes a further decline of the rural service sectors. Empirical tests of our major hypotheses using Korean census data from 1966, 1970, 1975, 1980 and 1985 support our own model much more than the neoclassical or Lipton's models. A kun (county) with a large out-migration had a smaller proportion of younger working aged people in the population, and a smaller proportion of highly educated workers. But the productivity of farm workers, measured in terms of fall crops (rice) purchased by the government per farmer or per hectare of irrigated land, did not decline despite the loss of these youths and of human capital. The kun having had a large out-migration had a larger proportion of the population in the farm sector and a smaller proportion in the service sector. The kun having had a large out-migration also had a lower income measured in terms of the proportion of households receiving welfare payments or the amount of provincial taxes paid per household. The lower incomes of these kuns might explain why the kuns that experienced a large out-migration had difficulty in mechanizing farming. Our policy suggestions based on the tests of the currently prevailing hypotheses are as follows: 1) The main cause of farming difficulties is not a lack of human capital, but the in­crease in production costs due to rural wage increases combined with depressed farm output prices. Therefore, a more effective way of helping farm economies is by increasing farm output prices. However, we are not sure whether an increase in farm output prices is desirable in terms of efficiency. 2) It might be worthwhile to attempt to increase the size of farmland holdings per farm household so that the mechanization of farming can be achieved more easily. 3) A kun with large out-migration suffers a deterioration in income and welfare. Therefore, the government should provide a form of subsidization similar to the adjustment assistance provided for international trade. This assistance should not be related to the level of farm output. Otherwise, there is a possibility that we might encourage farm production which would not be profitable in the absence of subsidies. 4) Government intervention in agricultural research and its dissemination, and large-scale social overhead projects in rural areas, carried out by the Korean government, might be desirable from both efficiency and equity points of view. Government interventions in research are justified because of the problems associated with the appropriation of knowledge, and government actions on large-scale projects are justified because they required collective action.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• Journal of Distribution Research
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• v.16 no.1
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• pp.95-115
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• 2011

Food service is the major part of franchise business in Korea, accounting for 69.9% of the brands in the market. As the food service industry becomes mature, many franchisees have struggled to survive in the market. In general, consumers have higher levels of expectation toward service quality of franchised outlets compared that of (non-franchised) independent ones. They also tend to believe that franchisees deliver standardized service at the uniform food price, regardless of their locations. Such beliefs seem to be important reasons that consumers prefer franchised outlets to independent ones. Nevertheless, few studies examined the impact of qualify features of franchisees on customer satisfaction so far. To this end, this study examined the characteristics of various quality features of franchisees in the food service industry, regarding their relationship with customer satisfaction and dissatisfaction. The quality perception of heavy-users was also compared with that of light-users in order to find insights for developing differentiated marketing strategy for the two segments. Customer satisfaction has been understood as a one-dimensional construct while there are recent studies that insist two-dimensional nature of the construct. In this regard, Kano et al. (1984) suggested to categorize quality features of a product or service into five types, based on their relation to customer satisfaction and dissatisfaction: Must-be quality, Attractive quality, One-dimensional quality, Indifferent quality, and Reverse quality. According to the Kano model, customers are more dissatisfied when Must-be quality(M) are not fulfilled, but their satisfaction does not arise above neutral no matter how fully the quality fulfilled. In comparison, customers are more satisfied with a full provision of Attactive quality(A) but manage to accept its dysfunction. One-dimensional quality(O) results in satisfaction when fulfilled and dissatisfaction when not fulfilled. For Indifferent quality(I), its presence or absence influences neither customer satisfaction nor dissatisfaction. Lastly, Reverse quality(R) refers to the features whose high degree of achievement results in customer dissatisfaction rather than satisfaction. Meanwhile, the basic guidelines of the Kano model have a limitation in that the quality type of each feature is simply determined by calculating the mode statistics. In order to overcome such limitation, the relative importance of each feature on customer satisfaction (Better value; b) and dissatisfaction (Worse value; w) were calculated following the formulas below (Timko, 1993). The Better value indicates how much customer satisfaction is increased by providing the quality feature in question. In contrast, the Worse value indicates how much customer dissatisfaction is decreased by providing the quality feature. Better = (A + O)/(A+O+M+I) Worse = (O+M)/(A+O+M+I)(-1) An on-line survey was performed in order to understand the nature of quality features of franchisees in the food service industry by applying the Kano Model. A total of twenty quality features (refer to the Table 2) were identified as the result of literature review in franchise business and a pre-test with fifty college students in Seoul. The potential respondents of our main survey was limited to the customers who have visited more than two restaurants/stores of the same franchise brand. Survey invitation e-mails were sent out to the panels of a market research company and a total of 257 responses were used for analysis. Following the guidelines of Kano model, each of the twenty quality features was classified into one of the five types based on customers' responses to a set of questions: "(1) how do you feel if the following quality feature is fulfilled in the franchise restaurant that you visit," and "(2) how do you feel if the following quality feature is not fulfilled in the franchise restaurant that you visit." The analyses revealed that customers' dissatisfaction with franchisees is commonly associated with the poor level of cleanliness of the store (w=-0.872), kindness of the staffs(w=-0.890), conveniences such as parking lot and restroom(w=-0.669), and expertise of the staffs(w=-0.492). Such quality features were categorized as Must-be quality in this study. While standardization or uniformity across franchisees has been emphasized in franchise business, this study found that consumers are interested only in uniformity of price across franchisees(w=-0.608), but not interested in standardizations of menu items, interior designs, customer service procedures, and food tastes. Customers appeared to be more satisfied when the franchise brand has promotional events such as giveaways(b=0.767), good accessibility(b=0.699), customer loyalty programs(b=0.659), award winning history(b=0.641), and outlets in the overseas market(b=0.506). The results are summarized in a matrix form in Table 1. Better(b) and Worse(w) index indicate relative importance of each quality feature on customer satisfaction and dissatisfaction, respectively. Meanwhile, there were differences in perceiving the quality features between light users and heavy users of any specific franchise brand in the food service industry. Expertise of the staffs was labeled as Must-be quality for heavy users but Indifferent quality for light users. Light users seemed indifferent to overseas expansion of the brand and offering new menu items on a regular basis, while heavy users appeared to perceive them as Attractive quality. Such difference may come from their different levels of involvement when they eat out. The results are shown in Table 2. The findings of this study help practitioners understand the quality features they need to focus on to strengthen the competitive power in the food service market. Above all, removing the factors that cause customer dissatisfaction seems to be the most critical for franchisees. To retain loyal customers of the franchise brand, it is also recommended for franchisor to invest resources in the development of new menu items as well as training programs for the staffs. Lastly, if resources allow, promotional events, loyalty programs, overseas expansion, award-winning history can be considered as tools for attracting more customers to the business.

• Journal of Nutrition and Health
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• v.47 no.6
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• pp.463-474
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• 2014

Purpose: The aim of this study was to assess the food environment, particularly focusing on restaurants in three areas (Suwon city, Hwaseong Byeongieom-dong, and Bibong-myun). Methods: A total of 662 persons were surveyed on customers' perceptions of the food environment in restaurants. A structured questionnaire composed of 30 questions on 7 factors, sanitation (4 items), displaying information (5), food quality (12), information on nutritional and healthy food choice (6), restaurant's accessibility (1), availability (1), and affordability (1) was used. In addition, an expert assessment of restaurant sanitation, and information on nutritional healthy food choice was conducted through visiting 126 restaurants. Results: Scores (range of score : 1~7) for each factors assessing the restaurant food environment were 5.06 for sanitation factors, 5.05 for displaying information factors, 5.13 for taste appearance factors, and 4.35 for healthy menu factors. Informations on nutritional healthy food choice showed a low rate: only 16.24% of the subjects answered that there is a message encouraging choice of healthy foods and 27.4% answered that menus contain nutritional information. Significant differences in food environment were observed by region (city, town, rural). The restaurants food environment in the rural area turned out to be poorer than that of the other two areas. In comparison of customer perception and expert assessment, significant differences were observed for 'Employee appearances and uniforms are clean and tidy' (p < .05), and 'There is a message encouraging the choice of healthy foods' (p < .05). Conclusion: This study provided evidence for differences of restaurant food environment by regions. In the rural area, there is a problem in restaurant's accessibility, availability, and affordability because of a lack of variety in menu items and restaurants. This results suggest that there is a need for more healthy food restaurants in the rural area.

• Journal of agricultural medicine and community health
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• v.23 no.2
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• pp.157-174
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• 1998

A survey was conducted to study the influence of socia-demographic factors on health-related behaviors. from June 1 to July 31, 1996. The study population was 1,903 adults in Kyongju City. A questionnaire method was used to collect data. Health-related behaviors included 24 items for men and 26 items for women. The followings are summaries of findings : The compliance of health promotion activities was higher when the age was older in men, when married, when having no religion and when the education level was higher than the other groups. And it was significantly higher when the income was lower in men and higher in women, in the residents living in apartment, in white collar workers, in the chronic ill people and when the body weight was lower than the other groups. Notable differences were found in the composition of health behavior factors for socio-demographic characteristics. Men used more tobacco, coffee and tea, salt and alcohol than women. However, the practice rates of regular exercise and physical examination were higher in men than women. On the other hand, the practice rates of fruit/vegetable intake, milk drinking and regular tooth brushing were higher in women than men. When the age was old, the amount of fruit/vegetable intake, the frequency of physician visit and health check-up, and regularity of meal were increased. When the income was high, the use rate of seat-belts, the amount of coffee, milk, fruit/vegetable and red meat intake were increased. The frequency of regular exercise. tooth brushing, health check-up, pap test and breast self examination were higher in the rich than the poor. When the education level was high, the frequency of regular exercise and tooth brushing, and the use rate of seat belts were increased, and the amount of alcohol consumption and salt intake were decreased. These findings suggest that socio-demographic factors are significantly associated with the patterns of health behaviors. In conclusion public health programs and individual counseling efforts should be multifaceted and behavior-specific to encourage to practice healthy life-style.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.