• Journal of Korean Home Economics Education Association
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• v.26 no.2
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• pp.31-49
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• 2014

The purpose of this study is to examine how the father involvement suggested in the Home Economics textbook through the development of gender-equal society and provide the basic data for the development of a standard for the father involvement in the viewpoint of gender equality. For this, the father involvement depicted in the main text, photos, and illustrations included in the Home Economics textbooks were examined. A total of 34 Home Economics textbooks written based on the curricula from the 1st Curriculum up to the 2007 Revised Curriculum were analyzed centering on the contents and the quantity of the text, supplementary materials, photos, and illustrations. The following are the results of the analysis. First, the Home Economics textbooks based on the 1st to 3rd Curriculua only described the traditional father involvement, and photos and illustrations did not specifically describe the role of the father. Second, the Home Economics textbooks based on the 4th to 5th Curricula began to show changes such as the image of the father sharing household responsibilities. Third, the Home Economics textbooks based on the 6th Curriculum suggested more active involvement of the father such as sharing the equal responsibility for the upbringing of children and sharing responsibilities for child care and housework. Fourth, the Home Economics textbooks based on the 7th Curricula up to the Revised Curriculum of 2007 emphasized the father's involvement of upbringing children. Especially, a variety of contents including the domestic responsibilities of the father, the correction of the "work-first" attitude, and gender equality related contents were suggested to promote gender-equal society further. Said results show that the contents related with gender equality and the descriptions about the father role in the viewpoint of gender equality are steadily increasing in Home Economics textbooks. However, there were still problems such as the gender-role division regarding the involvement of the father in the family and temporary responses to social demands. Open debates between the experts in the education of Home Economics and experts in family life may be required in order to improve said problems.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.45-67
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• 2016

Given the recent development of smart devices, users are producing, sharing, and acquiring a variety of information via the Internet and social network services (SNSs). Because users tend to use multiple media simultaneously according to their goals and preferences, domestic SNS users use around 2.09 media concurrently on average. Since the information provided by such media is usually textually represented, recent studies have been actively conducting textual analysis in order to understand users more deeply. Earlier studies using textual analysis focused on analyzing a document's contents without substantive consideration of the diverse characteristics of the source medium. However, current studies argue that analytical and interpretive approaches should be applied differently according to the characteristics of a document's source. Documents can be classified into the following types: informative documents for delivering information, expressive documents for expressing emotions and aesthetics, operational documents for inducing the recipient's behavior, and audiovisual media documents for supplementing the above three functions through images and music. Further, documents can be classified according to their contents, which comprise facts, concepts, procedures, principles, rules, stories, opinions, and descriptions. Documents have unique characteristics according to the source media by which they are distributed. In terms of newspapers, only highly trained people tend to write articles for public dissemination. In contrast, with SNSs, various types of users can freely write any message and such messages are distributed in an unpredictable way. Again, in the case of newspapers, each article exists independently and does not tend to have any relation to other articles. However, messages (original tweets) on Twitter, for example, are highly organized and regularly duplicated and repeated through replies and retweets. There have been many studies focusing on the different characteristics between newspapers and SNSs. However, it is difficult to find a study that focuses on the difference between the two media from the perspective of supply and demand. We can regard the articles of newspapers as a kind of information supply, whereas messages on various SNSs represent a demand for information. By investigating traditional newspapers and SNSs from the perspective of supply and demand of information, we can explore and explain the information dilemma more clearly. For example, there may be superfluous issues that are heavily reported in newspaper articles despite the fact that users seldom have much interest in these issues. Such overproduced information is not only a waste of media resources but also makes it difficult to find valuable, in-demand information. Further, some issues that are covered by only a few newspapers may be of high interest to SNS users. To alleviate the deleterious effects of information asymmetries, it is necessary to analyze the supply and demand of each information source and, accordingly, provide information flexibly. Such an approach would allow the value of information to be explored and approximated on the basis of the supply-demand balance. Conceptually, this is very similar to the price of goods or services being determined by the supply-demand relationship. Adopting this concept, media companies could focus on the production of highly in-demand issues that are in short supply. In this study, we selected Internet news sites and Twitter as representative media for investigating information supply and demand, respectively. We present the notion of News Value Index (NVI), which evaluates the value of news information in terms of the magnitude of Twitter messages associated with it. In addition, we visualize the change of information value over time using the NVI. We conducted an analysis using 387,014 news articles and 31,674,795 Twitter messages. The analysis results revealed interesting patterns: most issues show lower NVI than average of the whole issue, whereas a few issues show steadily higher NVI than the average.

• Journal of The Korean Association For Science Education
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• v.41 no.6
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• pp.455-470
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• 2021

This study examines the trend changes in keywords and topics of STEAM education from 2009 to 2020 to derive future development direction and education implications. Among the collected data, 42 cases of Ministry of Education's documents, 1,534 cases of articles, and 880 cases of abstract of researches were selected as research subjects. Keyword analysis, keyword network and topic modeling were performed for each stage of STEAM education policy through the Python program. As a result of the analysis, according to the STEAM education policy stage, there were differences in the frequency and network of keywords related to STEAM education by media. It was confirmed that there was a difference in interest in STEAM education policy as there were differences in keywords and topics that were mainly used importantly by media. Most of the topics of the Ministry of Education's documents were found to correspond to topics derived from articles. The implications for the development direction of STEAM education derived from the results of this study are as follows: first, STEAM education needs to consider ways to connect multiple topics, including the humanities. Second, since the media has a difference in interest in STEAM education policy, it is necessary to seek a cooperative development direction through understanding this. Third, the Ministry of Education's support for core competency reinforcement and convergence literacy for nurturing future talents, the goal of STEAM education, and the media's efforts to increase the public's understanding of STEAM education are required. Lastly, it is necessary to continuously analyze the themes that will appear in the evaluation process and change STEAM education policy.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.17-32
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• 2021

Speaker recognition is generally divided into speaker identification and speaker verification. Speaker recognition plays an important function in the automatic voice system, and the importance of speaker recognition technology is becoming more prominent as the recent development of portable devices, voice technology, and audio content fields continue to expand. Previous speaker recognition studies have been conducted with the goal of automatically determining who the speaker is based on voice files and improving accuracy. Speech is an important sociolinguistic subject, and it contains very useful information that reveals the speaker's attitude, conversation intention, and personality, and this can be an important clue to speaker recognition. The final ending used in the speaker's speech determines the type of sentence or has functions and information such as the speaker's intention, psychological attitude, or relationship to the listener. The use of the terminating ending has various probabilities depending on the characteristics of the speaker, so the type and distribution of the terminating ending of a specific unidentified speaker will be helpful in recognizing the speaker. However, there have been few studies that considered speech in the existing text-based speaker recognition, and if speech information is added to the speech signal-based speaker recognition technique, the accuracy of speaker recognition can be further improved. Hence, the purpose of this paper is to propose a novel method using speech style expressed as a sentence-final ending to improve the accuracy of Korean speaker recognition. To this end, a method called sentence sequencing that generates vector values by using the type and frequency of the sentence-final ending appearing in the utterance of a specific person is proposed. To evaluate the performance of the proposed method, learning and performance evaluation were conducted with a actual drama script. The method proposed in this study can be used as a means to improve the performance of Korean speech recognition service.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.287-316
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• 2023

As global energy crisis and the COVID-19 pandemic have emerged as social issues, there is a growing demand for companies to move away from profit-centric business models and embrace sustainable management that balances environmental, social, and governance (ESG) factors. ESG activities of companies vary across industries, and industry-specific weights are applied in ESG evaluations. Therefore, it is important to develop strategic management approaches that reflect the characteristics of each industry and the importance of each ESG factor. Additionally, with the stance of strengthened focus on ESG disclosures, specific guidelines are needed to identify and report on sustainable management activities of domestic companies. To understand corporate sustainability strategies, analyzing ESG reports and news articles by industry can help identify strategic characteristics in specific industries. However, each company has its own unique strategies and report structures, making it difficult to grasp detailed trends or action items. In our study, we analyzed ESG reports (2019-2021) and news articles (2019-2022) of six companies in the 'Finance,' 'Manufacturing,' and 'IT' sectors to examine the sustainability strategies of leading domestic ESG companies. Text mining techniques such as keyword frequency analysis and topic modeling were applied to identify industry-specific, ESG element-specific management strategies and issues. The analysis revealed that in the 'Finance' sector, customer-centric management strategies and efforts to promote an inclusive culture within and outside the company were prominent. Strategies addressing climate change, such as carbon neutrality and expanding green finance, were also emphasized. In the 'Manufacturing' sector, the focus was on creating sustainable communities through occupational health and safety issues, sustainable supply chain management, low-carbon technology development, and eco-friendly investments to achieve carbon neutrality. In the 'IT' sector, there was a tendency to focus on technological innovation and digital responsibility to enhance social value through technology. Furthermore, the key issues identified in the ESG factors were as follows: under the 'Environmental' element, issues such as greenhouse gas and carbon emission management, industry-specific eco-friendly activities, and green partnerships were identified. Under the 'Social' element, key issues included social contribution activities through stakeholder engagement, supporting the growth and coexistence of members and partner companies, and enhancing customer value through stable service provision. Under the 'Governance' element, key issues were identified as strengthening board independence through the appointment of outside directors, risk management and communication for sustainable growth, and establishing transparent governance structures. The exploration of the relationship between ESG disclosures in reports and ESG issues in news articles revealed that the sustainability strategies disclosed in reports were aligned with the issues related to ESG disclosed in news articles. However, there was a tendency to strengthen ESG activities for prevention and improvement after negative media coverage that could have a negative impact on corporate image. Additionally, environmental issues were mentioned more frequently in news articles compared to ESG reports, with environmental-related keywords being emphasized in the 'Finance' sector in the reports. Thus, ESG reports and news articles shared some similarities in content due to the sharing of information sources. However, the impact of media coverage influenced the emphasis on specific sustainability strategies, and the extent of mentioning environmental issues varied across documents. Based on our study, the following contributions were derived. From a practical perspective, companies need to consider their characteristics and establish sustainability strategies that align with their capabilities and situations. From an academic perspective, unlike previous studies on ESG strategies, we present a subdivided methodology through analysis considering the industry-specific characteristics of companies.

• Journal of Sinology and China Studies
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• v.81
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• pp.161-197
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• 2019

This paper aims to find out how rhetorical the rhetoric effect is in the speeches of the winners and runners-ups in the final round of the fifth final title. The subjects of this paper are the speeches of the winners and runner-ups who won the 5th and 10th finalist finals of "I Am a Speaker", which aired on Beijing TV on March 6, 2019. These speeches have images as well as texts, so we will look at the rhetorical expressions in the text and the speech and gesture language of the speakers. In addition, photographs presented as background data on stage when the winner and the runner-up each speak will be included in the analysis. In this paper, we will apply the "Rhetorical Sensitivity Scale", which quantifies the ability of persuasion as a methodology, and sets up the evaluation items based on the traditional theory of rhetoric and then analyzes two speeches. The traditional theory of rhetoric can be divided into five areas and three persuasive elements. The five areas include idea, disposition, expression, memory, and action delivery. The three persuasion elements are Ethos, Logos, and Pathos. In order to pursue objectivity as much as possible, this paper will proceed with both text analysis with verbal expression and video analysis with field situations at the time of speech.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.35 no.3
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• pp.32-40
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• 2017

The introduction of neo-Confucianism as the ideological foundation of Joseon, and its root Confucianism have become the origin of the life, scholarship and ideology of the Korean people. Additionally, it was considered the best to follow the teachings of the discipline's advocates including Confucius (孔子), Mencius (孟子), Zisi (子思), ZhuXi (朱子). Among these teachers, ZhuXi was the one who overtly presented the way of self-discipline, of which goal lies in attaining the character by the manifestation of vitality (氣 ki) and rationality (理 i) and contemplating on them. As he regarded natural places with mountains and waters as stages and tools for practicing toward the enlightenment, Confucian scholars in Joseon also followed his example in the spirit of honoring and studying ZhuXi (尊朱子, 學朱子), which became the basic thoughts and practical philosophy among them. Ryu, Junggyo, the neo-Confucian dogmatist, was no exception to applaud the nature, as he designated and ruled Okgye Gugok. On the basis of these backgrounds, this study aims to estimate the geographic places of Okgye Gugok, which was set by Ryu, Junggyo, a Confucian scholar in late-Joseon period, by collecting and analyzing the basic data, starting from Gareung-gun Okgye Sansugi(嘉陵郡玉溪山水記) which is the primary text authored by Seongjae Ryu, Junggyo. The literature study is followed by ten field trips to the estimated locations of Okgye Gugok, and verification of the estimations by three locals who were born and raised in Okgye Gugok. Coordinates and photographs were obtained as spatial data for each location of nine Gok(曲) estimated through this study. They will serve as a primary and critical data for story-telling and tourism resource in Okgye Gugok. The significance of this study is that it provides the primary data for designating the locations of Gok(曲) in Okgyeo Gugok.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.23-32
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• 2011

Design and Implementation of Clipcast Service via Terrestrial DMB This paper outlines the system design and the implementation process of clipcast service that can send clips of video, mp3, text, images, etc. to terrestrial DMB terminals. To provide clipcast service in terrestrial DMB, a separate data channel needs to be allocated and this requires changes in the existing bandwidth allocation. Clipcast contents can be sent after midnight at around 3 to 4 AM, when terrestrial DMB viewship is low. If the video service bit rate is lowered to 352 Kbps and the TPEG service band is fully used, then 320 Kbps bit rate can be allocated to clipcast. To enable clipcast service, the terminals' DMB program must be executed, and this can be done through SMS and EPG. Clipcast service applies MOT protocol to transmit multimedia objects, and transmits twice in carousel format for stable transmission of files. Therefore, 72Mbyte data can be transmitted in one hour, which corresponds to about 20 minutes of full motion video service at 500Kbps data rate. When running the clip transmitted through terrestrial DMB data channel, information regarding the length of each clip is received through communication with the CMS(Content Management Server), then error-free files are displayed. The clips can be provided to the users as preview contents of the complete VOD contents. In order to use the complete content, the user needs to access the URL allocated for that specific content and download the content by completing a billing process. This paper suggests the design and implementation of terrestrial DMB system to provide clipcast service, which enables file download services as provided in MediaFLO, DVB-H, and the other mobile broadcasting systems. Unlike the other mobile broadcasting systems, the proposed system applies more reliable SMS method to activate the DMB terminals for highly stable clipcast service. This allows hybrid, i.e, both SMS and EPG activations of terminals for clipcast services.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.509-520
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• 2015

College Scholastic Ability Test(CSAT) is a primary test to evaluate the study achievement of high-school students and used by most universities for admission decision in South Korea. Because its level of difficulty is a significant issue to both students and universities, the government makes a huge effort to have a consistent difficulty level every year. However, the actual levels of difficulty have significantly fluctuated, which causes many problems with university admission. In this paper, we build two types of data-driven prediction models to predict correct answer rate and to identify significant factors for CSAT English test through accumulated test data of CSAT, unlike traditional methods depending on experts' judgments. Initially, we derive candidate question-specific factors that can influence the correct answer rate, such as the position, EBS-relation, readability, from the annual CSAT practices and CSAT for 10 years. In addition, we drive context-specific factors by employing topic modeling which identify the underlying topics over the text. Then, the correct answer rate is predicted by multiple linear regression and level of difficulty is predicted by classification tree. The experimental results show that 90% of accuracy can be achieved by the level of difficulty (difficult/easy) classification model, whereas the error rate for correct answer rate is below 16%. Points and problem category are found to be critical to predict the correct answer rate. In addition, the correct answer rate is also influenced by some of the topics discovered by topic modeling. Based on our study, it will be possible to predict the range of expected correct answer rate for both question-level and entire test-level, which will help CSAT examiners to control the level of difficulties.

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

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