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Biodiversity and Community Composition of Benthic Macroinvertebrates from Upo Wetlands in Korea (우포습지의 저서성 대형무척추동물 다양성과 군집 특성)

  • 배연재;조신일;황득휘;이황구;나국본
    • Korean Journal of Environment and Ecology
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    • v.18 no.1
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    • pp.75-91
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    • 2004
  • Biodiversity and seasonal community composition of benthic macroinvertebrates were studied from Upo wetlands in Gyeongsangnam-do, Korea, comprising Upo (4 sites), Mokpo (2 sites), Sajipo (1 site), Jjokjibeol (1 site), Yeobeol (1 site), and Topyeongcheon (2 sites) areas from October 2002 to August 2003. As a result, it was known that Upo wetlands retained relatively well-preserved littoral zones which may provide good habitats for benthic macroinvertebrates; however, frequent disturbances of littoral zones caused by flood were the major factor affecting on the survival and distribution of benthic macroinvertebrates in the areas. During the study period, a total of 135 species of benthic macroinvertebrates in 10 genera, 59 families, 16 orders, 7 classes, and 3 phyla were collected those of which are the highest degree of diversity of the taxa ever known in Korean wetlands: aquatic insects 103 spp. (Diptera 27 spp., Odonata 24 spp., Coleoptera 19 spp., Hemiptera 16 spp., Ephemeroptera 9 spp., Trichoptera 7 spp., and Collembola 1 sp.), Crustacea 2 spp., Mollusca 19 spp. (Gastropoda 12 spp. and Bivalvia 7 spp.), and Annelids 11 spp. (Oligocaeta 1 sp. and Hirudinea 10 spp.). Sajipo (St.G) and Jjokjibeol (St.H) areas yielded relatively larger numbers of species, 54 spp. and 53 spp., respectively, while more than 40 species occurred at most other sites. Based on quantitative sampling (0.5m${\times}$2m), aquatic insects (88.0%), particularly chironomids in Diptera (61.0%), occupied major proportion of the total individuals of benthic macroinvertebrates, while Mollusca (5.3%), Annelida (3.5%), and Crustacea (3.2%) occupied minor proportions. In standing water areas, diverse groups of benthic macroinvertebrates such as chironomids, demselflies, aquatic bugs, aquatic beetles, crustaceans, and gastropods were dominant in terms of individual number; in the running water areas, on the other hand, chironomids and baetid mayflies were dominant. However, gastropods, i.e. viviparids, were the dominant group of benthic macroinvertebrates in most study areas in terms of biomass. Dominance indices were 0.22-0.51 (mean$\pm$sd 0.42$\pm$0.09) in autumn, 0.31-0.96 (0.02$\pm$0.23) in winter, and 0.30-0.89 (0.57$\pm$0.18) in summer; diversity indices were 3.50-4.26 (3.80$\pm$0.24) in autumn,1.55-4.50 (3.10$\pm$1.01) in winter, and 1.35-3.77 (2.55$\pm$0.09) in summer. Highly movable or true aquatic benthic macroinvertebyates such as aquatic bugs, aquatic beetles, and gastropods recovered earlier after flood. In the study sites of Upo wetlands, Upo and Sajipo areas showed relatively higher values of average diversity index which may indicate a good habitat condition for benthic macroinvertebrates.

Studies on a Plan for Afforestation at Tong-ri Beach Resort(II) -Analyses of Crown Amounts and Soil Properties in the Disaster-damage Prevention Forests of Pinus thunbergii PARL., the Valuation on Soil Properties for Planting and Planning for Afforestation- (통리(桶里) 해수욕장(海水浴場) 녹지대(綠地帶) 조성(造成)에 관(關)한 연구(硏究)(II) -곰솔 해안방재림(海岸防災林)의 수관량(樹冠量) 및 토양분석(土壤分析), 식재기반평가(植栽基盤評價) 및 녹지대계획(綠地帶計劃)-)

  • Cho, Hi Doo
    • Journal of Korean Society of Forest Science
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    • v.77 no.3
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    • pp.303-314
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    • 1988
  • Tong-ri beach has not enough vegetation to be enjoyed by the sea bathers and to be satisfied with preventing the disaster-damages, but mixed forest near the beach can work its funtions and the old forest of Pirus thunbergii $P_{ARL}$. near the beach do a Little. Therefore it is very urgent to plant more trees near the beach for bathers and disaster-damage prevention. This study was carried out for planning an afforestation, with reporting upon the crown amounts and soil properties of disaster-damage prevention forests of P. thunbergii $P_{ARL}$. planted on the coast sand dunes in 1970 and 1976, and with reporting upon the valuation on soil properties of the lands near the beach in order to set the afforestation site. The results are as follows : 1. In disaster-damage prevention forests, crown surface area and crown volume became increasingly greater in proportion to the height. To D.B.H., crown volume also became increasingly greater in proportion, but crown surface area was directly proportional. 2. In comparison to sail characteristics of sand dune, those of the forests were in large quantity in OM, T-N and avail. $SiO_2$, and almost in the same in avail. $P_2O_5$, but in small quantity in exchangeable canons : K, Ca, Mg and Na. 3. EC, Cl and pH were in small value in the forest soils, but CEC was in large value in those soils. 4. Above facts showed that the forests fulfill their functions for preventing disaster-damages and improve their soil properties. 5. The forests have naturally been thinned up to 34% in 17 years and 39% in 11 years, and one can easily pass through the forest(planted in 1970), because of its sufficient clear-length(2.71m) and its space to pass. 6. A plan for afforestation was oracle nut after judging several sites by the evaluation on the soil properties and considering the best relaxation and the prevention of the various disaster-damages upon which were reported in the last issue. 7. Afforestation should be kept for maintaining its appropriate density for best relaxation and disaster-damage prevention.

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If This Brand Were a Person, or Anthropomorphism of Brands Through Packaging Stories (가설품패시인(假设品牌是人), 혹통과고사포장장품패의인화(或通过故事包装将品牌拟人化))

  • Kniazeva, Maria;Belk, Russell W.
    • Journal of Global Scholars of Marketing Science
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    • v.20 no.3
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    • pp.231-238
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    • 2010
  • The anthropomorphism of brands, defined as seeing human beings in brands (Puzakova, Kwak, and Rosereto, 2008) is the focus of this study. Specifically, the research objective is to understand the ways in which brands are rendered humanlike. By analyzing consumer readings of stories found on food product packages we intend to show how marketers and consumers humanize a spectrum of brands and create meanings. Our research question considers the possibility that a single brand may host multiple or single meanings, associations, and personalities for different consumers. We start by highlighting the theoretical and practical significance of our research, explain why we turn our attention to packages as vehicles of brand meaning transfer, then describe our qualitative methodology, discuss findings, and conclude with a discussion of managerial implications and directions for future studies. The study was designed to directly expose consumers to potential vehicles of brand meaning transfer and then engage these consumers in free verbal reflections on their perceived meanings. Specifically, we asked participants to read non-nutritional stories on selected branded food packages, in order to elicit data about received meanings. Packaging has yet to receive due attention in consumer research (Hine, 1995). Until now, attention has focused solely on its utilitarian function and has generated a body of research that has explored the impact of nutritional information and claims on consumer perceptions of products (e.g., Loureiro, McCluskey and Mittelhammer, 2002; Mazis and Raymond, 1997; Nayga, Lipinski and Savur, 1998; Wansik, 2003). An exception is a recent study that turns its attention to non-nutritional packaging narratives and treats them as cultural productions and vehicles for mythologizing the brand (Kniazeva and Belk, 2007). The next step in this stream of research is to explore how such mythologizing activity affects brand personality perception and how these perceptions relate to consumers. These are the questions that our study aimed to address. We used in-depth interviews to help overcome the limitations of quantitative studies. Our convenience sample was formed with the objective of providing demographic and psychographic diversity in order to elicit variations in consumer reflections to food packaging stories. Our informants represent middle-class residents of the US and do not exhibit extreme alternative lifestyles described by Thompson as "cultural creatives" (2004). Nine people were individually interviewed on their food consumption preferences and behavior. Participants were asked to have a look at the twelve displayed food product packages and read all the textual information on the package, after which we continued with questions that focused on the consumer interpretations of the reading material (Scott and Batra, 2003). On average, each participant reflected on 4-5 packages. Our in-depth interviews lasted one to one and a half hours each. The interviews were tape recorded and transcribed, providing 140 pages of text. The products came from local grocery stores on the West Coast of the US and represented a basic range of food product categories, including snacks, canned foods, cereals, baby foods, and tea. The data were analyzed using procedures for developing grounded theory delineated by Strauss and Corbin (1998). As a result, our study does not support the notion of one brand/one personality as assumed by prior work. Thus, we reveal multiple brand personalities peacefully cohabiting in the same brand as seen by different consumers, despite marketer attempts to create more singular brand personalities. We extend Fournier's (1998) proposition, that one's life projects shape the intensity and nature of brand relationships. We find that these life projects also affect perceived brand personifications and meanings. While Fournier provides a conceptual framework that links together consumers’ life themes (Mick and Buhl, 1992) and relational roles assigned to anthropomorphized brands, we find that consumer life projects mold both the ways in which brands are rendered humanlike and the ways in which brands connect to consumers' existential concerns. We find two modes through which brands are anthropomorphized by our participants. First, brand personalities are created by seeing them through perceived demographic, psychographic, and social characteristics that are to some degree shared by consumers. Second, brands in our study further relate to consumers' existential concerns by either being blended with consumer personalities in order to connect to them (the brand as a friend, a family member, a next door neighbor) or by distancing themselves from the brand personalities and estranging them (the brand as a used car salesman, a "bunch of executives.") By focusing on food product packages, we illuminate a very specific, widely-used, but little-researched vehicle of marketing communication: brand storytelling. Recent work that has approached packages as mythmakers, finds it increasingly challenging for marketers to produce textual stories that link the personalities of products to the personalities of those consuming them, and suggests that "a multiplicity of building material for creating desired consumer myths is what a postmodern consumer arguably needs" (Kniazeva and Belk, 2007). Used as vehicles for storytelling, food packages can exploit both rational and emotional approaches, offering consumers either a "lecture" or "drama" (Randazzo, 2006), myths (Kniazeva and Belk, 2007; Holt, 2004; Thompson, 2004), or meanings (McCracken, 2005) as necessary building blocks for anthropomorphizing their brands. The craft of giving birth to brand personalities is in the hands of writers/marketers and in the minds of readers/consumers who individually and sometimes idiosyncratically put a meaningful human face on a brand.

Ensemble of Nested Dichotomies for Activity Recognition Using Accelerometer Data on Smartphone (Ensemble of Nested Dichotomies 기법을 이용한 스마트폰 가속도 센서 데이터 기반의 동작 인지)

  • Ha, Eu Tteum;Kim, Jeongmin;Ryu, Kwang Ryel
    • Journal of Intelligence and Information Systems
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    • v.19 no.4
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    • pp.123-132
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    • 2013
  • As the smartphones are equipped with various sensors such as the accelerometer, GPS, gravity sensor, gyros, ambient light sensor, proximity sensor, and so on, there have been many research works on making use of these sensors to create valuable applications. Human activity recognition is one such application that is motivated by various welfare applications such as the support for the elderly, measurement of calorie consumption, analysis of lifestyles, analysis of exercise patterns, and so on. One of the challenges faced when using the smartphone sensors for activity recognition is that the number of sensors used should be minimized to save the battery power. When the number of sensors used are restricted, it is difficult to realize a highly accurate activity recognizer or a classifier because it is hard to distinguish between subtly different activities relying on only limited information. The difficulty gets especially severe when the number of different activity classes to be distinguished is very large. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we take to dealing with this ten-class problem is to use the ensemble of nested dichotomy (END) method that transforms a multi-class problem into multiple two-class problems. END builds a committee of binary classifiers in a nested fashion using a binary tree. At the root of the binary tree, the set of all the classes are split into two subsets of classes by using a binary classifier. At a child node of the tree, a subset of classes is again split into two smaller subsets by using another binary classifier. Continuing in this way, we can obtain a binary tree where each leaf node contains a single class. This binary tree can be viewed as a nested dichotomy that can make multi-class predictions. Depending on how a set of classes are split into two subsets at each node, the final tree that we obtain can be different. Since there can be some classes that are correlated, a particular tree may perform better than the others. However, we can hardly identify the best tree without deep domain knowledge. The END method copes with this problem by building multiple dichotomy trees randomly during learning, and then combining the predictions made by each tree during classification. The END method is generally known to perform well even when the base learner is unable to model complex decision boundaries As the base classifier at each node of the dichotomy, we have used another ensemble classifier called the random forest. A random forest is built by repeatedly generating a decision tree each time with a different random subset of features using a bootstrap sample. By combining bagging with random feature subset selection, a random forest enjoys the advantage of having more diverse ensemble members than a simple bagging. As an overall result, our ensemble of nested dichotomy can actually be seen as a committee of committees of decision trees that can deal with a multi-class problem with high accuracy. The ten classes of activities that we distinguish in this paper are 'Sitting', 'Standing', 'Walking', 'Running', 'Walking Uphill', 'Walking Downhill', 'Running Uphill', 'Running Downhill', 'Falling', and 'Hobbling'. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window of the last 2 seconds, etc. For experiments to compare the performance of END with those of other methods, the accelerometer data has been collected at every 0.1 second for 2 minutes for each activity from 5 volunteers. Among these 5,900 ($=5{\times}(60{\times}2-2)/0.1$) data collected for each activity (the data for the first 2 seconds are trashed because they do not have time window data), 4,700 have been used for training and the rest for testing. Although 'Walking Uphill' is often confused with some other similar activities, END has been found to classify all of the ten activities with a fairly high accuracy of 98.4%. On the other hand, the accuracies achieved by a decision tree, a k-nearest neighbor, and a one-versus-rest support vector machine have been observed as 97.6%, 96.5%, and 97.6%, respectively.

Scale and Scope Economies and Prospect for the Korea's Banking Industry (우리나라 은행산업(銀行産業)의 효율성분석(效率性分析)과 제도개선방안(制度改善方案))

  • Jwa, Sung-hee
    • KDI Journal of Economic Policy
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    • v.14 no.2
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    • pp.109-153
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    • 1992
  • This paper estimates a translog cost function for the Korea's banking industry and derives various implications on the prospect for the Korean banking structure in the future based on the estimated efficiency indicators for the banking sector. The Korean banking industry is permitted to operate trust business to the full extent and the security business to a limited extent, while it is formally subjected to the strict, specialized banking system. Security underwriting and investment businesses are allowed in a very limited extent only for stocks and bonds of maturity longer than three year and only up to 100 percent of the bank paid-in capital. Until the end of 1991, the ceiling was only up to 25 percent of the total balance of the demand deposits. However, they are prohibited from the security brokerage business. While the in-house integration of security businesses with the traditional business of deposit and commercial lending is restrictively regulated as such, Korean banks can enter the security business by establishing subsidiaries in the industry. This paper, therefore, estimates the efficiency indicators as well as the cost functions, identifying the in-house integrated trust business and security investment business as important banking activities, for various cases where both the production and the intermediation function approaches in modelling the financial intermediaries are separately applied, and the banking businesses of deposit, lending and security investment as one group and the trust businesses as another group are separately and integrally analyzed. The estimation results of the efficiency indicators for various cases are summarized in Table 1 and Table 2. First, security businesses exhibit economies of scale but also economies of scope with traditional banking activities, which implies that in-house integration of the banking and security businesses may not be a nonoptimal banking structure. Therefore, this result further implies that the transformation of Korea's banking system from the current, specialized system to the universal banking system will not impede the improvement of the banking industry's efficiency. Second, the lending businesses turn out to be subjected to diseconomies of scale, while exhibiting unclear evidence for economies of scope. In sum, it implies potential efficiency gain of the continued in-house integration of the lending activity. Third, the continued integration of the trust businesses seems to contribute to improving the efficiency of the banking businesses, since the trust businesses exhibit economies of scope. Fourth, deposit services and fee-based activities, such as foreign exchange and credit card businesses, exhibit economies of scale but constant returns to scope, which implies, the possibility of separating those businesses from other banking and trust activities. The recent trend of the credit card business being operated separately from other banking activities by an independent identity in Korea as well as in the global banking market seems to be consistent with this finding. Then, how can the possibility of separating deposit services from the remaining activities be interpreted? If one insists a strict definition of commercial banking that is confined to deposit and commercial lending activities, separating the deposit service will suggest a resolution or a disappearance of banking, itself. Recently, however, there has been a suggestion that separating banks' deposit and lending activities by allowing a depository institution which specialize in deposit taking and investing deposit fund only in the safest securities such as government securities to administer the deposit activity will alleviate the risk of a bank run. This method, in turn, will help improve the safety of the payment system (Robert E. Litan, What should Banks Do? Washington, D.C., The Brookings Institution, 1987). In this context, the possibility of separating the deposit activity will imply that a new type of depository institution will arise naturally without contradicting the efficiency of the banking businesses, as the size of the banking market grows in the future. Moreover, it is also interesting to see additional evidences confirming this statement that deposit taking and security business are cost complementarity but deposit taking and lending businesses are cost substitute (see Table 2 for cost complementarity relationship in Korea's banking industry). Finally, it has been observed that the Korea's banking industry is lacking in the characteristics of natural monopoly. Therefore, it may not be optimal to encourage the merger and acquisition in the banking industry only for the purpose of improving the efficiency.

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Ensemble Learning with Support Vector Machines for Bond Rating (회사채 신용등급 예측을 위한 SVM 앙상블학습)

  • Kim, Myoung-Jong
    • Journal of Intelligence and Information Systems
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    • v.18 no.2
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    • pp.29-45
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    • 2012
  • Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

Predicting the Direction of the Stock Index by Using a Domain-Specific Sentiment Dictionary (주가지수 방향성 예측을 위한 주제지향 감성사전 구축 방안)

  • Yu, Eunji;Kim, Yoosin;Kim, Namgyu;Jeong, Seung Ryul
    • Journal of Intelligence and Information Systems
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    • v.19 no.1
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    • pp.95-110
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    • 2013
  • Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

Individual Thinking Style leads its Emotional Perception: Development of Web-style Design Evaluation Model and Recommendation Algorithm Depending on Consumer Regulatory Focus (사고가 시각을 바꾼다: 조절 초점에 따른 소비자 감성 기반 웹 스타일 평가 모형 및 추천 알고리즘 개발)

  • Kim, Keon-Woo;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.171-196
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    • 2018
  • With the development of the web, two-way communication and evaluation became possible and marketing paradigms shifted. In order to meet the needs of consumers, web design trends are continuously responding to consumer feedback. As the web becomes more and more important, both academics and businesses are studying consumer emotions and satisfaction on the web. However, some consumer characteristics are not well considered. Demographic characteristics such as age and sex have been studied extensively, but few studies consider psychological characteristics such as regulatory focus (i.e., emotional regulation). In this study, we analyze the effect of web style on consumer emotion. Many studies analyze the relationship between the web and regulatory focus, but most concentrate on the purpose of web use, particularly motivation and information search, rather than on web style and design. The web communicates with users through visual elements. Because the human brain is influenced by all five senses, both design factors and emotional responses are important in the web environment. Therefore, in this study, we examine the relationship between consumer emotion and satisfaction and web style and design. Previous studies have considered the effects of web layout, structure, and color on emotions. In this study, however, we excluded these web components, in contrast to earlier studies, and analyzed the relationship between consumer satisfaction and emotional indexes of web-style only. To perform this analysis, we collected consumer surveys presenting 40 web style themes to 204 consumers. Each consumer evaluated four themes. The emotional adjectives evaluated by consumers were composed of 18 contrast pairs, and the upper emotional indexes were extracted through factor analysis. The emotional indexes were 'softness,' 'modernity,' 'clearness,' and 'jam.' Hypotheses were established based on the assumption that emotional indexes have different effects on consumer satisfaction. After the analysis, hypotheses 1, 2, and 3 were accepted and hypothesis 4 was rejected. While hypothesis 4 was rejected, its effect on consumer satisfaction was negative, not positive. This means that emotional indexes such as 'softness,' 'modernity,' and 'clearness' have a positive effect on consumer satisfaction. In other words, consumers prefer emotions that are soft, emotional, natural, rounded, dynamic, modern, elaborate, unique, bright, pure, and clear. 'Jam' has a negative effect on consumer satisfaction. It means, consumer prefer the emotion which is empty, plain, and simple. Regulatory focus shows differences in motivation and propensity in various domains. It is important to consider organizational behavior and decision making according to the regulatory focus tendency, and it affects not only political, cultural, ethical judgments and behavior but also broad psychological problems. Regulatory focus also differs from emotional response. Promotion focus responds more strongly to positive emotional responses. On the other hand, prevention focus has a strong response to negative emotions. Web style is a type of service, and consumer satisfaction is affected not only by cognitive evaluation but also by emotion. This emotional response depends on whether the consumer will benefit or harm himself. Therefore, it is necessary to confirm the difference of the consumer's emotional response according to the regulatory focus which is one of the characteristics and viewpoint of the consumers about the web style. After MMR analysis result, hypothesis 5.3 was accepted, and hypothesis 5.4 was rejected. But hypothesis 5.4 supported in the opposite direction to the hypothesis. After validation, we confirmed the mechanism of emotional response according to the tendency of regulatory focus. Using the results, we developed the structure of web-style recommendation system and recommend methods through regulatory focus. We classified the regulatory focus group in to three categories that promotion, grey, prevention. Then, we suggest web-style recommend method along the group. If we further develop this study, we expect that the existing regulatory focus theory can be extended not only to the motivational part but also to the emotional behavioral response according to the regulatory focus tendency. Moreover, we believe that it is possible to recommend web-style according to regulatory focus and emotional desire which consumers most prefer.

Word-of-Mouth Effect for Online Sales of K-Beauty Products: Centered on China SINA Weibo and Meipai (K-Beauty 구전효과가 온라인 매출액에 미치는 영향: 중국 SINA Weibo와 Meipai 중심으로)

  • Liu, Meina;Lim, Gyoo Gun
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.197-218
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    • 2019
  • In addition to economic growth and national income increase, China is also experiencing rapid growth in consumption of cosmetics. About 67% of the total trade volume of Chinese cosmetics is made by e-commerce and especially K-Beauty products, which are Korean cosmetics are very popular. According to previous studies, 80% of consumer goods such as cosmetics are affected by the word of mouth information, searching the product information before purchase. Mostly, consumers acquire information related to cosmetics through comments made by other consumers on SNS such as SINA Weibo and Wechat, and recently they also use information about beauty related video channels. Most of the previous online word-of-mouth researches were mainly focused on media itself such as Facebook, Twitter, and blogs. However, the informational characteristics and the expression forms are also diverse. Typical types are text, picture, and video. This study focused on these types. We analyze the unstructured data of SINA Weibo, the SNS representative platform of China, and Meipai, the video platform, and analyze the impact of K-Beauty brand sales by dividing online word-of-mouth information with quantity and direction information. We analyzed about 330,000 data from Meipai, and 110,000 data from SINA Weibo and analyzed the basic properties of cosmetics. As a result of analysis, the amount of online word-of-mouth information has a positive effect on the sales of cosmetics irrespective of the type of media. However, the online videos showed higher impacts than the pictures and texts. Therefore, it is more effective for companies to carry out advertising and promotional activities in parallel with the existing SNS as well as video related information. It is understood that it is important to generate the frequency of exposure irrespective of media type. The positiveness of the video media was significant but the positiveness of the picture and text media was not significant. Due to the nature of information types, the amount of information in video media is more than that in text-oriented media, and video-related channels are emerging all over the world. In particular, China has made a number of video platforms in recent years and has enjoyed popularity among teenagers and thirties. As a result, existing SNS users are being dispersed to video media. We also analyzed the effect of online type of information on the online cosmetics sales by dividing the product type of cosmetics into basic cosmetics and color cosmetics. As a result, basic cosmetics had a positive effect on the sales according to the number of online videos and it was affected by the negative information of the videos. In the case of basic cosmetics, effects or characteristics do not appear immediately like color cosmetics, so information such as changes after use is often transmitted over a period of time. Therefore, it is important for companies to move more quickly to issues generated from video media. Color cosmetics are largely influenced by negative oral statements and sensitive to picture and text-oriented media. Information such as picture and text has the advantage and disadvantage that the process of making it can be made easier than video. Therefore, complaints and opinions are generally expressed in SNS quickly and immediately. Finally, we analyzed how product diversity affects sales according to online word of mouth information type. As a result of the analysis, it can be confirmed that when a variety of products are introduced in a video channel, they have a positive effect on online cosmetics sales. The significance of this study in the theoretical aspect is that, as in the previous studies, online sales have basically proved that K-Beauty cosmetics are also influenced by word-of-mouth. However this study focused on media types and both media have a positive impact on sales, as in previous studies, but it has been proven that video is more informative and influencing than text, depending on media abundance. In addition, according to the existing research on information direction, it is said that the negative influence has more influence, but in the basic study, the correlation is not significant, but the effect of negation in the case of color cosmetics is large. In the case of temporal fashion products such as color cosmetics, fast oral effect is influenced. In practical terms, it is expected that it will be helpful to use advertising strategies on the sales and advertising strategy of K-Beauty cosmetics in China by distinguishing basic and color cosmetics. In addition, it can be said that it recognized the importance of a video advertising strategy such as YouTube and one-person media. The results of this study can be used as basic data for analyzing the big data in understanding the Chinese cosmetics market and establishing appropriate strategies and marketing utilization of related companies.

Eurasian Naval Power on Display: Sino-Russian Naval Exercises under Presidents Xi and Putin (유라시아 지역의 해군 전력 과시: 시진핑 주석과 푸틴 대통령 체제 하에 펼쳐지는 중러 해상합동훈련)

  • Richard Weitz
    • Maritime Security
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    • v.5 no.1
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    • pp.1-53
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    • 2022
  • One manifestation of the contemporary era of renewed great power competition has been the deepening relationship between China and Russia. Their strengthening military ties, notwithstanding their lack of a formal defense alliance, have been especially striking. Since China and Russia deploy two of the world's most powerful navies, their growing maritime cooperation has been one of the most significant international security developments of recent years. The Sino-Russian naval exercises, involving varying platforms and locations, have built on years of high-level personnel exchanges, large Russian weapons sales to China, the Sino-Russia Treaty of Friendship, and other forms of cooperation. Though the joint Sino-Russian naval drills began soon after Beijing and Moscow ended their Cold War confrontation, these exercises have become much more important during the last decade, essentially becoming a core pillar of their expanding defense partnership. China and Russia now conduct more naval exercises in more places and with more types of weapons systems than ever before. In the future, Chinese and Russian maritime drills will likely encompass new locations, capabilities, and partners-including possibly the Arctic, hypersonic delivery systems, and novel African, Asian, and Middle East partners-as well as continue such recent innovations as conducting joint naval patrols and combined arms maritime drills. China and Russia pursue several objectives through their bilateral naval cooperation. The Treaty of Good-Neighborliness and Friendly Cooperation Between the People's Republic of China and the Russian Federation lacks a mutual defense clause, but does provide for consultations about common threats. The naval exercises, which rehearse non-traditional along with traditional missions (e.g., counter-piracy and humanitarian relief as well as with high-end warfighting), provide a means to enhance their response to such mutual challenges through coordinated military activities. Though the exercises may not realize substantial interoperability gains regarding combat capabilities, the drills do highlight to foreign audiences the Sino-Russian capacity to project coordinated naval power globally. This messaging is important given the reliance of China and Russia on the world's oceans for trade and the two countries' maritime territorial disputes with other countries. The exercises can also improve their national military capabilities as well as help them learn more about the tactics, techniques, and procedures of each other. The rising Chinese Navy especially benefits from working with the Russian armed forces, which have more experience conducting maritime missions, particularly in combat operations involving multiple combat arms, than the People's Liberation Army (PLA). On the negative side, these exercises, by enhancing their combat capabilities, may make Chinese and Russian policymakers more willing to employ military force or run escalatory risks in confrontations with other states. All these impacts are amplified in Northeast Asia, where the Chinese and Russian navies conduct most of their joint exercises. Northeast Asia has become an area of intensifying maritime confrontations involving China and Russia against the United States and Japan, with South Korea situated uneasily between them. The growing ties between the Chinese and Russian navies have complicated South Korean-U.S. military planning, diverted resources from concentrating against North Korea, and worsened the regional security environment. Naval planners in the United States, South Korea, and Japan will increasingly need to consider scenarios involving both the Chinese and Russian navies. For example, South Korean and U.S. policymakers need to prepare for situations in which coordinated Chinese and Russian military aggression overtaxes the Pentagon, obligating the South Korean Navy to rapidly backfill for any U.S.-allied security gaps that arise on the Korean Peninsula. Potentially reinforcing Chinese and Russian naval support to North Korea in a maritime confrontation with South Korea and its allies would present another serious challenge. Building on the commitment of Japan and South Korea to strengthen security ties, future exercises involving Japan, South Korea, and the United States should expand to consider these potential contingencies.

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