• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• Korean Journal of Environmental Agriculture
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• v.32 no.3
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• pp.214-223
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• 2013

BACKGROUND: This study focused on the development of an analytical method about dichlorprop (DCPP; 2-(2,4-dichlorophenoxy)propionic acid) which is a plant growth regulator, a synthetic auxin for agricultural commodities. DCPP prevents falling of fruits during their growth periods. However, the overdose of DCPP caused the unwanted maturing time and reduce the safe storage period. If we take fruits with exceeding maximum residue limits, it could be harmful. Therefore, this study presented the analytical method of DCPP in agricultural commodities for the nation-wide pesticide residues monitoring program of the Ministry of Food and Drug Safety. METHODS AND RESULTS: We adopted the analytical method for DCPP in agricultural commodities by gas chromatograph in cooperated with Electron Capture Detector(ECD). Sample extraction and purification by ion-associated partition method were applied, then quantitation was done by GC/ECD with DB-17, a moderate polarity column under the temperature-rising condition with nitrogen as a carrier gas and split-less mode. Standard calibration curve presented linearity with the correlation coefficient ($r^2$) > 0.9998, analysed from 0.1 to 2.0 mg/L concentration. Limit of quantitation in agricultural commodities represents 0.05 mg/kg, and average recoveries ranged from 78.8 to 102.2%. The repeatability of measurements expressed as coefficient of variation (CV %) was less than 9.5% in 0.05, 0.10, and 0.50 mg/kg. CONCLUSION(S): Our newly improved analytical method for DCPP residues in agricultural commodities was applicable to the nation-wide pesticide residues monitoring program with the acceptable level of sensitivity, repeatability and reproducibility.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Economic and Environmental Geology
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• v.40 no.2 s.183
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• pp.191-207
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• 2007

A paleomagnetic investigation for the Cretaceous rocks in the Buyeo and Hampyeong Basins, located out of the Gyeongsang Basin, was carried out in order to elucidate the paleomagnetic directions in conjunction with the formation of the basins. Typical stepwise thermal demagnetization and measurement methods were used to determine the directions of characteristic remanent magnetizations (ChRMs). The mean direction of the sedimentary rocks from the Buyeo Basin after bedding correction $(D/I=356.5^{\circ}/61.5^{\circ},\;k=39.3\;\alpha_{95}=7.4^{\circ})$, is more dispersed than that before bedding correction $(D/I=356.5^{\circ}/61.5^{\circ},\;k=39.3\;\alpha_{95}=7.4^{\circ})$, which suggests that the rocks in the Buyeo Basin were remagnetized. However, the statistics and dispersion of the ChRM directions after bedding correction are still acceptable and the paleomagnetic pole position after tilt correction $(Lat./Long.=69.3^{\circ}N/186.7^{\circ}E,\;K=11.6\;A_{95}=14.0^{\circ})$ is closer to that of the Late Cretaceous pole of the Korean Peninsula. More detailed study is needed to confirm the nature of the remagnetization in the Buyeo Basin. On the other hand, the paleomagnetic pole before bedding correction $(Lat./Long.=81.6^{\circ}N/106.9^{\circ}E,\;K=25.1\;A_{95}=9.3^{\circ})$ is positioned near the paleogene pole of the Eurasian APWP. The mean ChRM direction of the sedimentary rocks from the Hampyeong Basin after bedding correction is $D/I=32.5^{\circ}/55.4^{\circ},\;(k=35.6,\;\alpha_{95}=8.7^{\circ})$. It is more clustered than that before bedding correction $D/I=18.3^{\circ}/62.5^{\circ},\;k=14.1,\;\alpha_{95}=14.2^{\circ})$, indicating that the ChRM was acquired before tilting of the strata. The paleomagnetic pole position of the Cretaceous sedimentary rocks in the Hampyeong Basin, averaged out of site pole positions calculated from the tilt-corrected ChRMs, is $Lat./Long.=63.9^{\circ}N/202.7^{\circ}E,\;(K=21.3,\;A_{95}=7.6^{\circ})$, similar to the Late Cretaceous paleomagnetic pole of the Korean Peninsula $(Lat./Long.=70.9^{\circ}N/215.4^{\circ}E,\;A_{95}=5.3^{\circ})$, suggesting that the Hampyeong Basin has been stable since the Late Cretaceous period. One normal and two reversed ChRM directions are revealed through the measurements of the volcanic rocks from the Hampyeong Basin. Although these normal and reversed directions are not exactly antipodal, it is interpreted that the normal direction is the representative primary direction of the volcanic rocks of the Hampyeong Basin and the mixed polarity is the records of geomagnetic field at the time of the formation of the volcanic rocks. Paleomagnetic poles are at $Lat./Long.=70.2^{\circ}N/199.5^{\circ}E,\;(K=18.1,\;A_{95}=9.6^{\circ})$ for the normal direction, and $Lat./Long.=65.5^{\circ}S/251.3^{\circ}E,\;(K=7.1,\;A_{95}=20.7^{\circ})$ for the reversed direction. Compared with the representative pole positions of the Cretaceous period of the Korean Peninsula, it is concluded that the age of the volcanic rocks in the Hampyeong Basin is of the Late Cretaceous.

• (The)Study of the Eastern Classic
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• no.56
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• pp.147-170
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• 2014

To divide by the concept of Cheon (天) before and after the period of Song Dynasty: before Song Dynasty; according to the ancient Book of Odes (Sigyeong-詩經), "Cheon (天) gives birth to a large number of people", and, Confucius(孔子) say "Cheon(天) gave me Virtue(德)." Mencius(孟子) say "The person done with all his heart knows Seong(性, personality), so if he knows such Seong(性, personality), then he knows Cheon(天)." In Doctrine of the Mean(中庸), it says "Cheon(天) ordered it to be called - Seong(性, personality)." So, Cheon(天) had a religious meaning, such as Sangje(上帝) - Supreme Ruler. During the Song period, Cheon(天), the source of its existence, had construed as Mugeuk i Taegeuk Non(無極而太極論 - Theory of Supreme Ultimate while being Indeterminate) and Theory of li and ki (iginon-理氣論). Juja (朱子, a honorary name of Juhui, 朱熹) had said a reasonable Cheon(天), that is, Heavenly Principle (天理 - Cheolli) by interpreting Cheon(天) as Taegeuk(太極 - Supreme Polarity) and li(理) of Muwi(無爲 - uncontrived action). That's why Juja had lost the religiosity because of his reasonable frame. The purpose of this dissertation is to identify of the quality of being religious of li(理) on the basis of attribute of Cheon(天) argued by Toegye and Juja. In the text of Seomyeong(西銘 - Western Inscription), we can see their interpretation of the content that Toegye as "西銘考證講義"(Lecture on Historical Research of Western Inscription), and Juja as "西銘解"(Commentary on the Western Inscription). Seomyeong(西銘 - Western Inscription) was expounded as a logic of 'iil bunsu' (理一分殊 - coherence is one and distinguished into many). '理一分殊' means to live in as meaningful as possible according to the human nature that has been bestowed upon thyself. Juja and Toegye both said that in the aspect of 'iil'(理一 - coherence is one), Reverence(事天) ought to be done, but to look into the aspect of 'bunsu'(分殊-distinguished into many), Juja argued that people should follow the order of Heavenly Principle(天理 - Cheolli), and Toegye argued that people should have to perform the filial piety(孝). There are differences in methods of Toegye and Juja on account of distinction between attributes of Cheon(天). Such a distinction affects the attribute of li(理). Juja said divisively that Soiyeon(所以然-why its principle is so) is li(理), and Sodangyeon(所當然-what should be so) is Sa(事-divine project). Toegye argued that Sodangyeon(所當然-what should be so) is indeed li(理). It is the position of Toegye that to know Seong(性-the personality) of Sodangyeon(所當然-what should be so) is the first, rather than to know Cheon(天) of Soiyeon(所以然-why its principle is so) that is out of reach in a faraway place. Seong(性-the personality) is li(理) that bestowed by Cheon(天). In view of discussion about the essence and existence, for Toegye, the existence is the first, rather than the essence. The issues of existence is now enabled to talk about amid the discussion of metaphysics, namely li(理). Different from Juja, a theory noticed in Toegye is the theory of 'Lijado'(理自到). 'Lijado'(理自到) denotes 'Li(理) leads on their own.' It tells that separate from thing-in-itself, there is an energy that moves and oversees the thing. This is an issue of response between "I" as the principal agent and other people. If "I" as the principal agent is sincere to others, the others will come to me insomuch as they will be revealed through me. Here, a problem between the host and guest arises. Toegye perceived this problem that do not see me and others as same, and also do not see me and others as two. This is the logic of 'ilii iiil'(一而二 二而一 - looks like one but two, looks like two but one) of '理一分殊' (coherence is one and distinguished into many). The first thing to do between these two processes is to recognize the existence of 'iil'(理一). Toegye strongly displays a religious attitude identifying Cheon(天)=Li (理)=Sangje(上帝- Supreme Ruler) in the same light.