• Journal of the Health Care and Life Science
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• v.11 no.2
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• pp.261-269
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• 2023

The purpose of this study was to analyze the perception and practice of young children's health, which is emphasized in the stories of early childhood teachers. To collect data, telephone interviews were conducted with 15 teachers of kindergartens and daycare centers in Daejeon and Chungnam The collected data was analyzed by text network analysis. The research results are as follows. First, the participants observed the health of young children when they went to school, and contacted parents in case of abnormal signs. Second, the participants considered it important to understand the physical condition of children, proper nutrition intake, and manage health problems according to the characteristics of institutions where many people live together. Third, in relation to the management of infectious diseases, the participants were practicing to separate the child with symptoms from others, conduct disinfection and quarantine, and contact the parentst. Finally, the participants recognized that they should be educated related to safety in preparation for emergency, familiarize themselves with manuals in emergency situations, and know first aid methods according to the situation.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.456-466
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• 2014

This is a study of George Lindbeck's postliberalism that views religion as a cultural-linguistic approach. Knowing that the conceptual-propositional approach of the traditional Christian theology and the experiential-expressive approach of liberalism cannot be a solution for the post-modem religious phenomenon, George Lindbeck proposes an alternative. He proposes a cultural-linguistic approach to overcome the previous approaches. The first insight of Lindbeck's postliberalism is to understand religion as culture or language, because human beings become acquainted with a religion as they learn a language. The second insight comes out of the first, to understand doctrine as grammar. If we understand religion and doctrine this way the troubles and conflicts among religions will be resolved naturally, because each religion can be interpreted in its own system just as a language cannot be said to be good or bad, right or wrong. This approach makes several contributions as follows: it promotes a dialogue among religions, it emphasizes practice; and it preserves the Bible as an authoritative theological text. However it also brings many limitations as follows: it emphasizes the church's interpretation rather than the text's own interpretation; it views the truth simply as coherence; it promotes radical relativism and elitism; and through theological eschatology he makes his theory return to a propositionalism. Accordingly, the researcher concludes that Lindbeck's cultural-linguistic theory of religion is not an alternative that overcomes the limitations of theological conservativism and liberalism.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.4
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• pp.403-408
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• 2015

A text-based communication system has been developed with a communication function on AIS and display and input function on ECDIS as a way to complement voice communication. It features no linguistic error and is not affected by VHF restrictions on use and noise. The text communication system is designed to use messages for clear intentions and further improves convenience of users by using various UI through software. It works without additional hardware installation and modification and can transmit a sentence by selecting only via Message Banner Interface without keyboard input and furthermore has a advantage to enhance processing speed through its own message coding and decoding. It is determined as the most useful alternative to reduce language limitations and recognition errors of the user and solve the problem of various voice communications on VHF. In addition, it will help to prevent collisions between ships with decrease in VHF use, accurate communication and request of cooperation based on text at heavy traffic areas.

• Journal of Practical Engineering Education
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• v.5 no.2
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• pp.101-107
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• 2013

Clickers that are personal response systems are a technology used to promote active learning and most research on the benefits of using clickers has shown that students become engaged and enjoy using them. But, existing clickers consisting of hardware devices and aggregation software provide simple response and aggregation function and it costs a lot. In this paper, in order to resolve the limitation of the existing clickers, we've designed and implemented the Smart Clicker consisting of a smartphone application for students and a web application & a MFC program for professors. Students can answer professor's questions with O/X or numbers or text and even ask questions with text messaging by using Smart Clicker in the classroom. Professors can see students' answers or questions immediately and check up students' response participation rate on the web page. Besides, the Smart Clicker will help professors actively engage students during the entire class period and gauge their level of understanding of the material being presented, and provide prompt feedback to student questions. As a result, we expect that quality of education will be increased.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.145-151
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• 2020

'Hansik', or Korean cuisine is one of Korea national brands. To understand the domestic consumer awareness of Korean cuisine, data was gathered under the keyword search, 'Hansik.' Textom 3.5 was used to gather data from blogs, news media found on Naver from November 1, 2018, to October 31, 2019. The results from frequency and TF-IDF analysis indicate that the 'buffet' had the largest proportion in terms of consumer awareness to Hansik. Also, broadcasting contents starring star chefs had a great influence. The Hansik awareness did not remain in the domains of its traditionality, but also branched into extents into areas such as fusional and gourmet cuisine. UCINET6 and NetDraw were used to conduct CONCOR analysis. Four cluster formations have been found; various food cultural cluster, high-end restaurant cluster referring to aired restaurants on media, Hansik brand cluster, and Hansik buffet cluster. This study proposes presenting a various menu of Hansik which use a multiple number of ingredients. Also, a promotion that introduces fine Hansik and a development of marketing views and media contents about the convenient HMRs make the associated imagery of Hansik to be strengthen.

• Korean Journal of Cognitive Science
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• v.17 no.4
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• pp.337-356
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• 2006

This research was conducted to see the impact of brightness, polarity, and hue diference on legibility and emotional effcts of the word. In the experiment 1, stimuli with three levels of brightness difference and two-typed polarity were used. The results showed that legibility, aesthetics, and preference increased with increasing brightness difference. In the experiment 2, the same stimuli if experiment 1 included four hues: red, green, blue, yellow. As a result, the effects of brightness and polarity and the interaction effect of brightness and polarity on legibility were significant. Also, the effects of brightness, polarity, and hue and the interaction effect of brightness and hue on aesthetics and preference were significant. These results showed that legibility, aesthetics, and preference increased with increasing brightness difference of word and background and positive polarity was better than negative. Aesthetics and preference rating increased according to the following order: red, blue, green, yellow. In addition, the interaction effect of brightness and polarity on legibility was because reaction time of negative polarity was longer than positive at the small brightness difference condition. The interaction effect of brightness and hue on aesthetics and preference ws because the aesthetics rating of hue at the large brightness difference condition had significant difference compared with small brightness difference. In the experiment 3, participants rated text designs and simple color stimuli with 18 emotional adjectives to see the similarity of their emotion. The conclusion was that to reflect the subjective feelings of a rotor on the text design, it would be appropriate to use the rotor on background of the text design.

• Korean Journal of Cognitive Science
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• v.26 no.4
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• pp.435-452
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• 2015

Recent researches on Entity Linking(EL) have attempted to disambiguate entities by using a knowledge base to handle the semantic relatedness and up-to-date information. However, EL for tweets using a knowledge base is still unsatisfactory, mainly because the tweet data are mostly composed of short and noisy contexts and real-time issues. The EL system the present work builds up links ambiguous entities to the corresponding entries in a given knowledge base via exploring the news articles and the user history. Using news articles, the system can overcome the problem of Wikipedia coverage (i.e., not handling real-time issues). In addition, given that users usually post tweets related to their particular interests, the current system referring to the user history robustly and effectively works with a small size of tweet data. In this paper, we propose an approach to building an EL system that links ambiguous entities to the corresponding entries in a given knowledge base through the news articles and the user history. We created a dataset of Korean tweets including ambiguous entities randomly selected from the extracted tweets over a seven-day period and evaluated the system using this dataset. We use accuracy index(number of correct answer given by system/number of data set) The experimental results show that our system achieves a accuracy of 67.7% and outperforms the EL methods that exclusively use a knowledge base.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.121-131
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• 2017

With emergence of Internet, social media, and mobile service, the consumers have actively presented their opinions and sentiment, and then it is spreading out real time as well. The user-generated text data on the Internet and social media is not only the communication text among the users but also the valuable resource to be analyzed for knowing the users' intent and sentiment. In special, economic participants have strongly asked that the social big data and its' analytics supports to recognize and forecast the economic trend in future. In this regard, the governments and the businesses are trying to apply the social big data into making the social and economic solutions. Therefore, this study aims to reveal the capability of social big data analysis for the economic use. The research proposed a social big data analysis model and an online consumer sentiment index. To test the model and index, the researchers developed an economic survey ontology, defined a sentiment dictionary for sentiment analysis, conducted classification and sentiment analysis, and calculated the online consumer sentiment index. In addition, the online consumer sentiment index was compared and validated with the composite consumer survey index of the Bank of Korea.