• KDI Journal of Economic Policy
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• v.32 no.2
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• pp.171-216
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• 2010

With the payment and settlement systems becoming more and more complex and interconnected, the issue of their interdependency rises as an important academic issue as well as a policy topic. This study examines causes, forms, and risk management of interdependencies of payment and settlement systems in Korea, and presents their current situation. By way of simulations using BOF-PSS2 developed by the Bank of Finland, we quantify the effects of an operational disruption on the payment and settlement systems so as to figure out the degree of interdependency. As a result, the secondary round effect reaches up to ￦13.6 trillion a day, which amounts to 7.8% of the daily settlement value. Furthermore, if we also consider the amount of direct operational disruption, the volume of operational disruption occupies 22.3% of total value of the daily settlement, evidencing that the interdependencies of the payment and settlement systems in Korea is enormously widespread. The secondary round effects are found to be more severe with security companies rather than with banks, and to be more depended upon when it is perceived rather than it actually happens. In case that we expand the liquidity to include cash holdings and deposits as assets, the secondary round effect dramatically decreases in all types of financial institutions while foreign banks account for more share of all the secondary round effects increases. Based on these results, we suggest various policy tasks and directions to improve the risk management of settlement systems: expansion of off-setting settlements, introduction of a new settlement system for securities transactions, rapid provision of liquidity to financial institutions, more effective monitoring on participant institutions, and intensified information sharing and cooperation among the systems.

• Journal of Dairy Science and Biotechnology
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• v.33 no.2
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• pp.111-118
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• 2015

Probiotic, prebiotic, and synbiotic substances as well as microorganisms were added to infant formula in an attempt to influence the intestinal microflora with an aim to stimulate the growth of lactic acid bacteria, especially bifidobacteria and lactobacilli. Over the last 10 years, new synbiotic infant formulas containing probiotics and prebiotics have been proposed in order to simulate the effect of breast-feeding on the intestinal microflora. Owing to their synergistic effect, the new synbiotics are expected to be more helpful than using probiotics and prebiotics individually. Maintenance of the viability of the probiotics during food processing and the passage through the gastrointestinal tract should be the most important consideration, since a sufficient number of bacteria ($10^8cfu/g$) should reach the intended location to have a positive effect on the host. Storage conditions and the processing technology used for the manufacture of products such as infant formula adversely affect the viability of the probiotics. When an appropriate and cost-effective microencapsulation methodology using the generally recognized as safe (GRAS) status and substances with high biological value are developed, the quality of infant formulas would improve. The effect of probiotics may be called a double-effect, where one is an immunomodulatory effect, induced by live probiotics that advantageously alter the gastrointestinal microflora, and the other comprises anti-inflammatory responses elicited by dead cells. At present, a new terminology is required to define the dead microorganisms or crude microbial fractions that positively affect health. The term "paraprobiotics" (or ghost probiotics) has been proposed to define dead microbial cells (not damaged or broken) or crude cell extracts (i.e., cell extracts with complex chemical composition) that are beneficial to humans and animals when a sufficient amount is orally or topically administered. The fecal microflora of bottle-fed infants is altered when the milk-based infant formula is supplemented with probiotics or prebiotics. Thus, by increasing the proportion of beneficial bacteria such as bifidobacteria and lactobacilli, prebiotics modify the fecal microbial composition and accordingly regulate the activity of the immune system. Therefore, considerable attention has been focused on the improvement of infant formula quality such that its beneficial effects are comparable to those of human milk, using prebiotics such as inulin and oligosaccharides and potential specific probiotics such as bifidobacteria, which selectively stimulate the proliferation of beneficial bacteria in the microflora and the indigenous intestinal metabolic activity of the microflora.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2003.05a
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• pp.91-93
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• 2003

A comprehensive numerical study is carried out to investigate for the understanding of the flow evolution and flame development in a supersonic combustor with normal injection of ncumally injecting hydrogen in airsupersonic flows. The formulation treats the complete conservation equations of mass, momentum, energy, and species concentration for a multi-component chemically reacting system. For the numerical simulation of supersonic combustion, multi-species Navier-Stokes equations and detailed chemistry of H2-Air is considered. It also accommodates a finite-rate chemical kinetics mechanism of hydrogen-air combustion GRI-Mech. 2.11[1], which consists of nine species and twenty-five reaction steps. Turbulence closure is achieved by means of a k-two-equation model (2). The governing equations are spatially discretized using a finite-volume approach, and temporally integrated by means of a second-order accurate implicit scheme (3-5).The supersonic combustor consists of a flat channel of 10 cm height and a fuel-injection slit of 0.1 cm width located at 10 cm downstream of the inlet. A cavity of 5 cm height and 20 cm width is installed at 15 cm downstream of the injection slit. A total of 936160 grids are used for the main-combustor flow passage, and 159161 grids for the cavity. The grids are clustered in the flow direction near the fuel injector and cavity, as well as in the vertical direction near the bottom wall. The no-slip and adiabatic conditions are assumed throughout the entire wall boundary. As a specific example, the inflow Mach number is assumed to be 3, and the temperature and pressure are 600 K and 0.1 MPa, respectively. Gaseous hydrogen at a temperature of 151.5 K is injected normal to the wall from a choked injector.A series of calculations were carried out by varying the fuel injection pressure from 0.5 to 1.5MPa. This amounts to changing the fuel mass flow rate or the overall equivalence ratio for different operating regimes. Figure 1 shows the instantaneous temperature fields in the supersonic combustor at four different conditions. The dark blue region represents the hot burned gases. At the fuel injection pressure of 0.5 MPa, the flame is stably anchored, but the flow field exhibits a high-amplitude oscillation. At the fuel injection pressure of 1.0 MPa, the Mach reflection occurs ahead of the injector. The interaction between the incoming air and the injection flow becomes much more complex, and the fuel/air mixing is strongly enhanced. The Mach reflection oscillates and results in a strong fluctuation in the combustor wall pressure. At the fuel injection pressure of 1.5MPa, the flow inside the combustor becomes nearly choked and the Mach reflection is displaced forward. The leading shock wave moves slowly toward the inlet, and eventually causes the combustor-upstart due to the thermal choking. The cavity appears to play a secondary role in driving the flow unsteadiness, in spite of its influence on the fuel/air mixing and flame evolution. Further investigation is necessary on this issue. The present study features detailed resolution of the flow and flame dynamics in the combustor, which was not typically available in most of the previous works. In particular, the oscillatory flow characteristics are captured at a scale sufficient to identify the underlying physical mechanisms. Much of the flow unsteadiness is not related to the cavity, but rather to the intrinsic unsteadiness in the flowfield, as also shown experimentally by Ben-Yakar et al. [6], The interactions between the unsteady flow and flame evolution may cause a large excursion of flow oscillation. The work appears to be the first of its kind in the numerical study of combustion oscillations in a supersonic combustor, although a similar phenomenon was previously reported experimentally. A more comprehensive discussion will be given in the final paper presented at the colloquium.

• Journal of the Korean Geographical Society
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• v.40 no.3 s.108
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• pp.296-309
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• 2005

In this study, we investigated the change of future land-surface and relationships of land-surface change with geo-spatial information, using a Bayesian prediction model based on a likelihood ratio function, for analysing the land-surface change of the Gongju area. We classified the land-surface satellite images, and then extracted the changing area using a way of post classification comparison. land-surface information related to the land-surface change is constructed in a GIS environment, and the map of land-surface change prediction is made using the likelihood ratio function. As the results of this study, the thematic maps which definitely influence land-surface change of rural or urban areas are elevation, water system, population density, roads, population moving, the number of establishments, land price, etc. Also, thematic maps which definitely influence the land-surface change of forests areas are elevation, slope, population density, population moving, land price, etc. As a result of land-surface change analysis, center proliferation of old and new downtown is composed near Gum-river, and the downtown area will spread around the local roads and interchange areas in the urban area. In case of agricultural areas, a small tributary of Gum-river or an area of local roads which are attached with adjacent areas showed the high probability of change. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the capability of forest damage is very high. As a result of validation using a prediction rate curve, a capability of prediction of urban area is $80\%$, agriculture area is $55\%$, forest area is $40\%$ in higher $10\%$ of possibility which the land-surface change would occur. This integration model is unsatisfactory to Predict the forest area in the study area and thus as a future work, it is necessary to apply new thematic maps or prediction models In conclusion, we can expect that this way can be one of the most essential land-surface change studies in a few years.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.69-85
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• 2016

Successful relationship with loving partners is one of the most important factors in life. In psychology, there have been some previous researches studying the factors influencing romantic relationships. However, most of these researches were performed based on statistical analysis; thus they have limitations in analyzing complex non-linear relationships or rules based reasoning. This research analyzes commitment and persistence in heterosexual involvement according to styles of loving using a datamining technique as well as statistical methods. In this research, we consider six different styles of loving - 'eros', 'ludus', 'stroge', 'pragma', 'mania' and 'agape' which influence romantic relationships between lovers, besides the factors suggested by the previous researches. These six types of love are defined by Lee (1977) as follows: 'eros' is romantic, passionate love; 'ludus' is a game-playing or uncommitted love; 'storge' is a slow developing, friendship-based love; 'pragma' is a pragmatic, practical, mutually beneficial relationship; 'mania' is an obsessive or possessive love and, lastly, 'agape' is a gentle, caring, giving type of love, brotherly love, not concerned with the self. In order to do this research, data from 105 heterosexual couples were collected. Using the data, a linear regression method was first performed to find out the important factors associated with a commitment to partners. The result shows that 'satisfaction', 'eros' and 'agape' are significant factors associated with the commitment level for both male and female. Interestingly, in male cases, 'agape' has a greater effect on commitment than 'eros'. On the other hand, in female cases, 'eros' is a more significant factor than 'agape' to commitment. In addition to that, 'investment' of the male is also crucial factor for male commitment. Next, decision tree analysis was performed to find out the characteristics of high commitment couples and low commitment couples. In order to build decision tree models in this experiment, 'decision tree' operator in the datamining tool, Rapid Miner was used. The experimental result shows that males having a high satisfaction level in relationship show a high commitment level. However, even though a male may not have a high satisfaction level, if he has made a lot of financial or mental investment in relationship, and his partner shows him a certain amount of 'agape', then he also shows a high commitment level to the female. In the case of female, a women having a high 'eros' and 'satisfaction' level shows a high commitment level. Otherwise, even though a female may not have a high satisfaction level, if her partner shows a certain amount of 'mania' then the female also shows a high commitment level. Finally, this research built a prediction model to establish whether the relationship will persist or break up using a decision tree. The result shows that the most important factor influencing to the break up is a 'narcissistic tendency' of the male. In addition to that, 'satisfaction', 'investment' and 'mania' of both male and female also affect a break up. Interestingly, while the 'mania' level of a male works positively to maintain the relationship, that of a female has a negative influence. The contribution of this research is adopting a new technique of analysis using a datamining method for psychology. In addition, the results of this research can provide useful advice to couples for building a harmonious relationship with each other. This research has several limitations. First, the experimental data was sampled based on oversampling technique to balance the size of each classes. Thus, it has a limitation of evaluating performances of the predictive models objectively. Second, the result data, whether the relationship persists of not, was collected relatively in short periods - 6 months after the initial data collection. Lastly, most of the respondents of the survey is in their 20's. In order to get more general results, we would like to extend this research to general populations.

• Korean Business Review
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• v.13
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• pp.49-66
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• 2000

Despite the fact that understanding customers satisfaction with transportation services is a subject of great importance, authors, so far, found no systematic researches referred to that issue. From this point, studying the satisfaction with subways services can be extremely useful. Empirical study of key factors in the satisfaction with subway services is the departure point, which holds as objectives, and we believe, will contribute to overall increasing in the number of subways services used and in the amount of public benefits derived from that usage. In order to achieve these goals: First, several items referred to some key factors in the satisfaction of subway usage were systemized. Second, a research of specific weights attached to those key factors by subway passengers was conducted. Knowledge of the satisfaction variables system can provide deep insights into ones perceptual experience when using a subway. The results were as follows: Various interrelated factors compose a passengers satisfaction with subway services. People do not just use subway passively; a number of key factors, like physical and personal services, exact timing, easiness to access etc. determine the passengers satisfaction with subway. In order to find out specific weights of these key factors multiple regression analysis was employed. Results showed that satisfaction with subway is determined by (in order of importance) easiness to access, quality of physical services, friendliness of working stuff and timing exactness. According to the findings, passengers do not use subway as a simple mean of transportation, rather they perceive it as a complex combination of environmental elements and overall satisfaction depends on these various factors. Therefore, to learn passengers satisfaction with subways services, passengers subway experience must be thoroughly studied and analyzed, and this is where papers value resides.

• Tuberculosis and Respiratory Diseases
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• v.45 no.2
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• pp.351-359
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• 1998

Background: The effects of exercise on pulmonary function are complex and have been the subject of many investigations. But, there has been disputes about the effect of exercise on spirometric parameters and there is no study about the effect of exercise on IOS(Impulse Oscillometry)parameters. IOS, a new method of pulmonary function test, is based on the relationship between the pressure and flow oscillation which is produced by applying sinusoidal pressure oscillation to the respiratory system via the mouth. Method: Fifty-nine young adults without respiratory symptoms were divided into three groups according to degree of exercise(hard exercise group: mean exercise time is over three hours per week at least for the last one month, light exercise group : between thirty minutes to three hours, nonexercise group : less than thirty minutes) and undertaken pulmonary function test(simple spirometry and IOS). Results: The effects of exercise on spirometric parameters; percentage of predictive value of forced vital capacity(FVC % pred) was higher in hard exercise group than nonexercise group(hard exercise group: $102.4{\pm}14.8$, nonexercise group: $93.7{\pm}9.9$, p=0.017), but there was no significant difference in percentage of predicted value of forced expiratory volume in one second(FEV 1 % pred) and percentage of predicted value of forced expiratory flow 50% (FEF 50% pred) between groups. The effects of exercise on IOS parameters: Reactance at 5Hz(X5) was significantly lower in hard exercise group than nonexercise group(hard exercise group: $-0.166{\pm}0.123hPa/1/s$, nonexercise group: $-0.093{\pm}0.036hPa/1/s$, p=0.006) but there was no significant difference in central resistance(Rc), peripheral resistance(Rp), resonance frequency(RF) and resistance at 5Hz, 20Hz between groups. Conclusion: Hard exercise increased FVC % pred on spirometric parameters and decreased reactance at 5Hz(X5) on IOS parameters.

• The Korean Journal of Nuclear Medicine
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• v.37 no.4
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• pp.235-244
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• 2003

Purpose: Attention deficit hyperactivity disorder (ADHD) has been known as psychiatric disorder in childhood associated with dopamine dysregulation. In present study, we investigated changes in dopamine transporter (DAT) density of the basal ganglias using I-123 N-(3-iodopropen-2-yl) -2-carbomethoxy-3beta-(4-chlorophenyl) tropane [I-123 IPT] SPECT in children with ADHD before and after methylphenidate treatment. Materials and Method: Nine drug-naive children with ADHD and seven normal children were included in the study. We peformed brain SPECT two hours after the intravenous administration of I-123 IPT and made both quantitative and qualitative analyses using the obtained SPECT data, which were reconstructed for the assessment of soecific/nonspecific DAT binding ratios in the basal ganglia. All children with ADHD reperformed [123I]IPT SPECT after treatment with methylphenidate(0.7mg/kg/d) during about 8 weeks. SPECT data reconstructed for the assessment of specific/nonspecific DAT binding ratio of the basal ganglia were compared between before and after treatment methylphenidate. We investigated correlation between the change of ADHD symptom severity assessed with ADHD rating scale-IV and specific/nonspecific DAT binding ratio of basal ganglia. Results: Children with ADHD had a significantly greater specificinonspecific DAT binding ratio of the basal ganglia comparing to normal children(Right : z = 2.057, p = 0.041 : Left : z : 2.096, p = 0.032). Under treatment with methylphenidate in all children with ADHD, specificinonspecific DAT binding ratio of both basal ganglia decreased significantly greater than before treatment with methylphenidate (Right : t = 3.239, p = 0.018 ; Left : t = 3.133, p = 0.020). However, no significant correlation between the change of ADHD symptom severity scores and specific/nonspecific DAT binding ratio of the basal ganglia were found. Conclusions: These findings support the complex dysregulation of the dopaminergic neurotransmitter system in children with ADHD.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.77-92
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• 2014

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.119-138
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• 2017

Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.