• Journal of Service Research and Studies
• /
• v.13 no.3
• /
• pp.127-146
• /
• 2023

Recently, digital advertising has shifted towards delivering messages through short ads of less than 15 seconds, and on social media, ads need to convey the message within 5 seconds before consumers skip them. Although the length of advertisements has decreased, advancements in artificial intelligence algorithms and big data analysis have made it possible to deliver personalized messages that cater to consumers' interests. In this changing landscape, the importance of delivering tailored messages through short and efficient ads is increasing. In this study, we examined the effects of message framing as part of effective message delivery. Specifically, we examined the differences in the effects of two framings, "health" and "environment," for vegan products. The growing consumer interest in health and the environment has elevated the interest in vegan products, and the vegan market is expanding rapidly. Consumers purchase vegan products not only for personal health benefits but also due to their ethical responsibility towards the environment, which can be considered ethical consumption. Previous research has not shown the differences in the effects between health and environment message framings, and the research has been limited to vegan food products. This study investigates the differences in the effects of health and environment message framings using a dish soap product category. By identifying which advertising messages, either health or environment, are more effective in promoting vegan products, this study provides insights for companies to enhance their message framing strategies effectively.

• Economic Analysis
• /
• v.26 no.3
• /
• pp.71-133
• /
• 2020

The Bank of Korea began its operation on June 12, 1950, with the Bank of Korea Act established a month or so earlier. Thus was first introduced to Korea modern central banking in the real sense of the word. The Bloomfield Mission, consisting of A. Bloomfield and J. Jensen of the Federal Reserve Bank of New York, spent about six months drafting a bill, which finally became the Bank of Korea Act. Little has been known yet about the process leading to the creation of the Mission and the historical context surrounding it, except that F. Tamagna of the Federal Reserve Board made in his capacity of the ECA's representative the offer of technical assistance to the Korean government. This paper attempts to dig deeper into relevant historical records and literature to fill these gaps. As it happened, the confrontation between the US and the USSR was accelerating towards the end of 1940s. The paper's new findings include that the Bloomfield Mission was, together with the ECA Mission to Korea, a product of the then US foreign policy (Cold War policy) and that the former Mission's technical assistance was conceived and provided all along as part of the inflation stabilization program pursued by the latter Mission. The Bloomfield Mission was after all a historical necessity. Next, the paper examines the changes added to the bill during its journey to becoming the Bank of Korea Act enacted in May 1950, presenting a review of the Act. The paper further evaluates the Act in terms of legal persistence, finding that the revised Act currently in force still substantially resembles the Act enacted 70 years ago from now. Finally in order is a brief discussion on those factors which seem to have contributed much to such persistence and thus apparent excellence of the Act enacted.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.6 no.4
• /
• pp.169-179
• /
• 2016

This study was to investigate special education teachers' teaching in reading and writing to university students with intellectual disabilities. For this study, we surveyed 71special education teachers who work in Gwangju, Daegu and Busan. As a result, in order to identify students' reading and writing abilities, they were more likely to use their own tests which they made for themselves than standardized tests. When teaching students, they used their own teaching experiences and advices from colleagues and senior teachers regarding problem-solving methods and reliable information while the knowledge they learned at school showed low frequency in use. Despite using mainly whole-word approach when instructing reading and writing, it appeared that teachers' teaching experiences and diversity of textbooks also have an influence. Regarding needs of education participation for teaching students, there were high needs and interests in teaching methods of writing, textbooks and teaching materials by the characteristics of disability, reading and writing development, reading and writing disabilities. In case of difficulties and needs in teaching students, there was a high demand of development of a wide variety of teaching materials and tools and, preparation for sufficient textbooks and test tools, while difficulties in teaching appeared in lack of knowledge about reading and writing, lack of screening/evaluating tools, and evaluating and teaching oriented to each disability characteristic.

• Design Convergence Study
• /
• v.15 no.2
• /
• pp.347-368
• /
• 2016

Recently, researches for the word of mouth(WOM) imply that consumers use WOM informations of products in their purchase process. This study suggests methods using opinion mining and visualization to understand consumers' opinion of each goods and each markets. For this study we conduct research that includes developing domain ontology based on reviews confined to "movie" category because people who want to have watching movie refer other's movie reviews recently, and it is analyzed by opinion mining and visualization. It has differences comparing other researches as conducting attribution classification of evaluation factors and comprising verbal dictionary about evaluation factors when we conduct ontology process for analyzing. We want to prove through the result if research method will be valid. Results derived from this study can be largely divided into three. First, This research explains methods of developing domain ontology using keyword extraction and topic modeling. Second, We visualize reviews of each movie to understand overall audiences' opinion about specific movies. Third, We find clusters that consist of products which evaluated similar assessments in accordance with the evaluation results for the product. Case study of this research largely shows three clusters containing 130 movies that are used according to audiences'opinion.

• Journal of the Korean Institute of Rural Architecture
• /
• v.24 no.4
• /
• pp.85-95
• /
• 2022

This study is about the story of 'Saemi', existing in the Sacheon Alluvial fan area. Saemi is a local word for Dumbeong, which is the traditional water irrigation facilities in this area that could be formed according to the geographical characteristics of a Alluvial fan site. In the meantime, although Saemi has been an important source of water, related research has been mainly done from an ecological point of view. Accordingly, the researcher paid attention to the functional aspects of Saemi itself, grasped its location, distribution status, and usage including the construction method, and considered its intrinsic value through classification and characteristic analysis of Saemi. As a result of five field surveys from September 2021 to October 2022, 129 Saemies remained in the Sacheon alluvial fan area. According to the structure and shape, Saemi could be divided into basic type, complex type, and buried type. The basic type was subdivided into bucket-type and stairs-type along with the complex type, and the buried type was subdivided into all buried-type and some buried-type. Saemies were mainly distributed at the distal end of the Sacheon alluvial fan site, individual Saemies were built on farmland, and common Saemies were usually built along roadsides adjacent to villages. The reason why the Saemies are concentrated at the distal end is the geographical characteristics of the alluvial fan where the water underflows. Saemi was an important multifunctional water supply source equivalent to the main water source for people at the distal end of the pond who did not receive a stable supply of water from the reservoir. Saemi was at the center of the underground water irrigation network agricultural system in the Sacheon alluvial fan area according to the principles of 'bbaeim(drop out)' and 'gaepim(pooling)' It has provided a foundation for establishing itself as an appropriate technology in this area. Such Saemi contributed to the rural landscape and agricultural biodiversity through its own system and served as a public interest function. It is necessary to know, conserve, manage, and continuously utilize the value of this Saemi as an agricultural heritage.

• Science of Emotion and Sensibility
• /
• v.25 no.4
• /
• pp.3-20
• /
• 2022

The origins of the world-recognized Korean gat can be traced back to Gojoseon, and the jades for the sangtu and gwanja come from Hongshan culture. This study examines the etymology of the hat, the symbolism of the gat and the jade comb, and the history of the development of the accessories for the hat. The research methods of literature review, investigation of relics and murals, and analysis of cases of pronunciation changes were used. Most of the relics excavated from the Hongshan are identical to those excavated from Korea. The Byun-Khan people wore a triangle-shaped conical hat (the byun), which was shaped to fit the protruding sangtu hairstyle, with a foldable brim that, if pulled downward, changed the hat to a gat. The Chu sangtu, a pointed top-knot hairstyle, is uniquely found among Northeast Asian peoples, and it is an ethnic symbol for Koreans. Until the modern period, many Koreans wore their hair in the sangtu style, indicating their descent from the sky. Jade combs shaped like birds and clouds from the Hongshan period emphasized the religious nature and ceremony of hair styling at that period. The word hat is widely used to refer to gat all over the world. The pronunciation of ㄱg, ㅎh. and ㅋq/kh are closely related to each other, and the ancient pronunciation ㄱg gradually evolved to ㅎh or ㅋq/kh. The English 'Hat' and Korean 'Gat' were transformed from the middle-ancient sound 'gasa > gosa > got' of the crown 'gwan, gokkal'. This creative hair style culture that started from the Hongshan culture continued to be fashionable during the Gojoseon Dangun period, and the decoration techniques for hats and accessories were inherited over time and continuously developed. Along with the method of making gat, creative hair-related parts, such as manggeons, donggot pins, gwanja buttons, and fine combs were developed over the course of a thousand years.

• Korean Journal of Culture and Social Issue
• /
• v.13 no.2
• /
• pp.17-32
• /
• 2007

The word "Loss" means being deprived a person's meaningful property, people or idea by irresistible force, and it is not avoidable in one's life. Especially, the elderly have higher possibility to experience this "Loss" than any other age groups on account of their characteristics. Feeling grief of loss after going through any kind of loss is natural and normal. However, if someone has severe trouble with overcoming this grief, it would affect negatively to his/her psychological or social inelastic. Therefore, we tried to find out which factors consists the "Grief of loss" and how it affects on the elderly's quality of life, especially on the sense of ego-integrity through this study. 97 of the elderly over age 65 participated in the survey and the results as follow; grief of loss is classified into four factors, 'economical loss', 'loss from being parted by death', 'loss of physical functions' and 'loss of relations'. These four factors of "Grief of loss" showed negative correlations with the scores of the sense of ego-integrity factors except 'acceptance of death'. Especially, the 'economical loss' affects on every factor of the sense of ego-integrity negatively except 'acceptance of death' and 'acceptance of aging'. Moreover, 'loss of physical functions' and 'loss of relations' affect negatively on elderly's satisfaction to their lives. On the other hand, the 'loss from being parted by death' of "Grief of loss" and 'acceptance of death' of the sense of ego-integrity showed no statistically significant effect in every process of analysis.

• Information Systems Review
• /
• v.25 no.1
• /
• pp.93-110
• /
• 2023

Recently, attempts have been made to convert unstructured text into vectors and to analyze vast amounts of natural language for various purposes. In particular, the demand for analyzing texts in specialized domains is rapidly increasing. Therefore, studies are being conducted to analyze specialized and general-purpose documents simultaneously. To analyze specific terms with general terms, it is necessary to align the embedding space of the specific terms with the embedding space of the general terms. So far, attempts have been made to align the embedding of specific terms into the embedding space of general terms through a transformation matrix or mapping function. However, the linear transformation based on the transformation matrix showed a limitation in that it only works well in a local range. To overcome this limitation, various types of nonlinear vector alignment methods have been recently proposed. We propose a vector alignment model that matches the embedding space of specific terms to the embedding space of general terms through end-to-end learning that simultaneously learns the autoencoder and regression model. As a result of experiments with R&D documents in the "Healthcare" field, we confirmed the proposed methodology showed superior performance in terms of accuracy compared to the traditional model.

• The Korean Journal of Applied Statistics
• /
• v.37 no.4
• /
• pp.395-410
• /
• 2024

Text data is usually made up of a wide variety of unique words. Even in standard text data, it is common to find tens of thousands of different words. In text data analysis, usually, each unique word is treated as a variable. Thus, text data can be regarded as a dataset with a large number of variables. On the other hand, in text data classification, we often encounter class label imbalance problems. In the cases of substantial imbalances, the performance of conventional classification models can be severely degraded. To improve the classification performance of support vector machines (SVM) for imbalanced data, algorithms such as the Synthetic Minority Over-sampling Technique (SMOTE) can be used. The SMOTE algorithm synthetically generates new observations for the minority class based on the k-Nearest Neighbors (kNN) algorithm. However, in datasets with a large number of variables, such as text data, errors may accumulate. This can potentially impact the performance of the kNN algorithm. In this study, we propose a method for enhancing prediction performance for the minority class of imbalanced text data. Our approach involves employing variable selection to generate new synthetic observations in a reduced space, thereby improving the overall classification performance of SVM.

• Journal of Intelligence and Information Systems
• /
• v.22 no.3
• /
• pp.45-69
• /
• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.