• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.1-17
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• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.

• Journal of The Korean Association For Science Education
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• v.25 no.4
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• pp.441-449
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• 2005

The purpose of this study was to examine the degree of cognitive conflict by learner personality and the method of presenting anomalous data to induce cognitive conflict. The participants of this study were 461 high school students. To arose cognitive conflict, an actual demonstration was done for half of the participants and a logical article for the rest. MBTI (Myers-Briggs Type Indicator) was used to find the learner personality types, and CCLT (Cognitive Conflict Level Test) was used to measure the degree of cognitive conflict aroused when anomalous data was confronted. The results of this study indicated that learner personality types influence the degree of cognitive conflict. First, participants were divided into two personality types via preferences on each of the four preference indices; extraversion (E) or introversion (I), sensing (S) or intuition (N), thinking (T) or feeling (F), judgment (J) or perception (P). The cognitive conflict scores of the thinking types were significantly higher than those of the feeling types. Participants were also divided four personality types according to personality functional types: ST, SF, NT and NF. SF type showed a significantly lower cognitive conflict score than any of the other types. According to the type of learner personality, cognitive conflict was influenced differently by the method of presenting anomalous data. For example, the judgment types had a higher cognitive conflict score by logical argument, and the perception types showed a higher score by demonstration. In conclusion, learner cognitive conflicts were influenced by personality types and the methods of presenting anomalous data.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.47-60
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• 2010

Most of the researches about classification usually have used kNN(k-Nearest Neighbor), SVM(Support Vector Machine), which are known as learn-based model, and Bayesian classifier, NNA(Neural Network Algorithm), which are known as statistics-based methods. However, there are some limitations of space and time when classifying so many web pages in recent internet. Moreover, most studies of classification are using uni-gram feature representation which is not good to represent real meaning of words. In case of Korean web page classification, there are some problems because of korean words property that the words have multiple meanings(polysemy). For these reasons, LSA(Latent Semantic Analysis) is proposed to classify well in these environment(large data set and words' polysemy). LSA uses SVD(Singular Value Decomposition) which decomposes the original term-document matrix to three different matrices and reduces their dimension. From this SVD's work, it is possible to create new low-level semantic space for representing vectors, which can make classification efficient and analyze latent meaning of words or document(or web pages). Although LSA is good at classification, it has some drawbacks in classification. As SVD reduces dimensions of matrix and creates new semantic space, it doesn't consider which dimensions discriminate vectors well but it does consider which dimensions represent vectors well. It is a reason why LSA doesn't improve performance of classification as expectation. In this paper, we propose new LSA which selects optimal dimensions to discriminate and represent vectors well as minimizing drawbacks and improving performance. This method that we propose shows better and more stable performance than other LSAs' in low-dimension space. In addition, we derive more improvement in classification as creating and selecting features by reducing stopwords and weighting specific values to them statistically.

• Journal of the Korean earth science society
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• v.28 no.2
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• pp.169-178
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• 2007

In this research we diagnosed the actual status of the 7th National science elective curriculum and suggested a way to select and organize the content of the new science elective curriculum. The first science education reform was grounded in the structuralism where the structure of discipline was valued above everything else. On the other hand, the second science education reform suggested alternative interpretations of students' opportunity to learn, putting a brake on the structuralist thinking. According to the survey result, the majority of the science elective courses are in need for revision because the contents are overcrowded, too difficult in light of students' learning readiness, failed to draw students' interest in science, and are overlapped and repeated among the 10th grade science, high school science I and II. In particular, Earth Science II and physics II are the most unfavorable courses among students. Thus, we recommended a fundamental change be made in the new curriculum in addition to the optimization of the content. In this paper, we suggested 'topic-centered content organization' for the science elective course I, i.e., Physics I, Chemistry I, Biology I and Earth Science I that is designed for both science track and non-science track students. Since curriculum provides students with an 'opportunity to learn', a curriculum study should focus on what the 'opportunity to learn' is that students ought to be offered. Based on the result of this study, we recommended one way to select and organize the content of high school elective curriculum.

• Journal of Korean Home Economics Education Association
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• v.23 no.1
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• pp.159-176
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• 2011

The purpose of this study was to investigate 1) how the middle school Home Economics teachers perceive the importance of the practical problem-focused instruction, 2) how often they perform the instruction, and 3) what they require for the implementation the instruction. Data were collected from 150 Home Economics teachers via e-mail survey and from 6 Home Economics teachers' face-to-face interviews. Descriptive statistics including frequency, percentage, average, and standard deviation, and the results of such analyses as ANOVA, T-test, and correlation were reported using SPSS/win 10.1. The results of this research were as follows: First, even though the majority of the respondents recognized the high need for practical problem-focused instruction, only a small portion of the respondents reported that they performed that instruction in the classroom. There was no correlation between the perception of the need for practical problem-focused instruction and the degree of performance of practical problem-focused instruction. Secondly, the of performance of practical problem-focused instruction was significantly different depending on the years of teaching experience and the subject that the teachers majored in. Job satisfaction had positive correlations with the perception of the need for practical problem-focused instruction and the degree of performance of practical problem-focused instruction. Thirdly, the more teachers shared information and materials with colleagues, the better they tended to be at practical problem-focused instruction. On the other hand, insufficient time for their instruction and a deficiency in understanding the rationale of the instruction were pointed out as barriers to classroom practice. The respondents answered that long-term training programs on the philosophical foundation of practical problem-focused instruction, materials related to the instruction as well as additional credits for Home Economics are most critical to reduce the discrepancy between the teacher perception and the classroom practice of practical problem-focused instruction.

• Journal of Korean Home Economics Education Association
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• v.22 no.4
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• pp.91-107
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• 2010

The purpose of this study was to investigate what middle school Home Economics(HE) teachers perceive, practice and need for self-supervision at school related to HE. Questionnaires were sent by E-mail and 150 were collected. Descriptive statistics including frequency, percentage, average, standard deviation, t-test and ANOVA analysis were reported using SPSS/win 10.1. The results of this research were as follows: First, middle school HE teachers perceived that self-supervision at school was essential since it promoted self reflection of teachers themselves and improved professional skills. Furthermore, peer-coaching was highly preferred. Second, negative responses to the supervision of principal, vice-principal, and peer teachers overwhelmed positive answers. Information exchange among peer teachers was frequent, yet, approximately 22.6% of middle school HE teachers were still avoiding sharing information process for several reasons. About half of the teachers answered that all teachers needed to participate in this process. Third, they pointed out that self-supervision at school was not implemented well because of the lack of time due to the heavy work load, negative and passive attitude for the improvement of teaching-learning activities, administration-centered supervision that did not reflect teachers' opinion, and shortage of economical, and environmental support.. HE teachers perceived that peer teachers who were doing good practices were most helpful for the supervision. Also, they preferred self-evaluation at the end of the self-supervision at school. Forth, to improve self-supervision at school, there were very high demands for reduction of administrative work, additional time, fundamental philosophy toward HE education. Fifth, the purpose and detailed plans of self-supervision were recognized as the results that were democratically derived by the HE teachers. Sixth, class inspection and informal inspection were operated once in a year, and self-training was rarely operated. Peer coaching and self-coaching were operated occasionally. Self-coaching and peer coaching were reported as the most helpful types of supervision. In addition, HE teachers answered that supervision was helpful to teaching method followed by contents, evaluation, and philosophy of education.

• 대한공업교육학회지
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• v.33 no.2
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• pp.192-217
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• 2008

This paper investigated the perceived criticalities and patterns of Korean Professional Engineer's competency regarding the working activities of automative product development, manufacturing, etc by using questionnaires responded to the survey which were applied to the automotive professors, experts and professional engineers (vocational parties) by e/mail, etc. This research investigated the following questions: First, what are the characteristic patterns, relevancy and perceived criticalities of Korean Professional Engineer's competencies? Second, What are the ranked priority of the Korean Professional Engineers' competencies? Are there any differency for each item, sub group of job, intelectual criterior of the competencies between relevancy and perceived criticalities according to the types of vocational parties, etc.? Accoring to the results; first, Professor group showed highest points among 3 groups per each item of the competencies by vocational parties Second, Chassis design group ranked top position among the 8 sub groups by vocational parties and, third, Problem Solving Knowledge ranked highest points than any others. Korean Professional Engineers are found to be positioned as key members, leaders and managers on surveying market, product planning, designing product & components, developing component parts, establishing shop with production equipment, managing quality control & material handling, organizing relevant meetings, developing human resources by training and learning, to back up finance with law matters, cooperating with concerned parties to achieve organizational goals, and to coordinate projects. etc, identifying ethical issues and business skills in order to survive and win to be competitive in various kinds of the automotive industry battle fields.

• Investigative Magnetic Resonance Imaging
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• v.17 no.4
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• pp.294-307
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• 2013

Purpose : To investigate the correlations between Seoul Neuropsychological Screening Battery (SNSB) scores and the gray matter volumes (GMV) in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) and cognitively normal (CN) elderly subjects with correcting the genotypes. Materials and Methods: Total 75 subjects were enrolled with 25 subjects for each group. The apolipoprotein E (APOE) epsilon genotypes, SNSB scores, and the 3D T1-weighted images were obtained from all subjects. Correlations between SNSB scores and GMV were investigated with the multiple regression method for each subject group using both voxel-based and region-of-interest-based analyses with covariates of age, gender, and the genotype. Results: In the AD group, Rey Complex Figure Test (RCFT) delayed recall scores were positively correlated with GMV. In the MCI group, Seoul Verbal Learning Test (SVLT) scores were positively correlated with GMV. In the CN group, GMV negatively correlated with Boston Naming Test (K-BNT) scores and Mini-Mental State Examimation (K-MMSE) scores, but positively correlated with RCFT scores. Conclusion: When we used covariates of age, gender, and the genotype, we found statistically significant correlations between some SNSB scores and GMV at some brain regions. It may be necessary to further investigate a longitudinal study to understand the correlation.

• Journal of Science Education
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• v.38 no.3
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• pp.718-736
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• 2014

This study was intended to determine PCK of the middle school science teachers on Mendelian genetics and factors influenced to form their PCKs. Two science teachers with biology major with a teaching experience over 5 years were chosen as the subject. Data were collected by class observation, semi-structured interview, teacher questionnaire survey, Content Representation and Pedagogical and Professional-experience Repertoire. The collected data were analyzed based on Magnusson's PCK for science teaching consisting of five components: (a) the orientation toward teaching science, (b) the knowledge of science curriculum, (c) the knowledge of students' understanding, (d) the knowledge of assessment, and (e) the knowledge and belief in the instructional strategies to teach science. Teachers could have the orientation toward teaching science served as an assisting role to support students' abilities. Both subject teachers seemed to focus on giving lectures. Their efforts to improve students' exploration methods and abilities were not expressed enough in their real classes and they found that students struggled to understand Mendelian genetics. Therefore, they should have explained them in an easier way and worked harder to make their students understood accurately and applied basic and advanced concepts of Mendelian genetics. They found students' preconception and misconception regarding Mendelian genetics and wished to enhance their learning effects by various teaching strategies such as correcting misconception, adding the history of science and simply assessing students' affirmative domains. It was also found that factors influenced to form PCK regarding Mendelian genetics by both teachers were as follows: teacher's personality and endeavor, textbooks and guidance books, schools and their circumstances, teaching experience, experience as a learner, interaction with their colleagues, and university curriculum. Both teachers said that it was important for teachers to make every efforts to give better classes.