• Korea Science and Art Forum
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• v.21
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• pp.31-43
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• 2015

Information and Communications Technology (ICT) is one of the technologies which represent the core value of the creative economy. It has served as a vehicle connecting the existing industry and corporate infrastructure, developing existing products and services and creating new products and services. In addition to the ICT, new devices including big data, mobile gadgets and wearable products are gaining a great attention sending an expectation for a new market-pioneering. Further, Internet of Things (IoT) is helping solidify the ICT-based social development connecting human-to-human, human-to-things and things-to-things. This means that the manufacturing-based hardware development needs to be achieved simultaneously with software development through convergence. The essential element the convergence between hardware and software is OS, for which world's leading companies such as Google and Apple have launched an intense development recognizing the importance of software. Against this backdrop, the status-quo of the software market has been examined for the study of the present report (Korea Evaluation Institute of Industrial Technology: Professional Design Technology Development Project). As a result, the software platform-based Google's android and Apple's iOS are dominant in the global market and late comers are trying to enter the market through various pathways by releasing web-based OS and similar OS to provide a new paradigm to the market. The present study is aimed at finding the way to utilize a smart content by which anyone can be a developer based on OS responding to such as social change, newly defining a smart content to be universally utilized and analyzing the market to deal with a rapid market change. The study method, scope and details are as follows: Literature investigation, Analysis on the app market according to a smart classification system, Trend analysis on the current content market, Identification of five common trends through comparison among the universal definition of smart content, the status-quo of application represented in the app market and content market situation. In conclusion, the smart content market is independent but is expected to develop in the form of a single organic body being connected each other. Therefore, the further classification system and development focus should be made in a way to see the area from multiple perspectives including a social point of view in terms of the existing technology, culture, business and consumers.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.285-294
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• 2017

In this study, change of the view of love was analyzed by big data analysis in TV drama of married person's love. Two dramas were selected for analysis with opposite theme of love story. The sympathy of audience for the one month period from the end of the drama was analyzed by text mining and sentiment analysis. In particular, changes in the meaning of home meaning are identified. Home is not 'a place where a husband and wife play a social role', but 'a place where they can share real sympathy and one can be happy'. If individuals are not happy, they need to break their homes. In this study, the current divorce rate and the question regarding the matter should be considered. But based on Google Trends, in Korean society, interest in marriage were still higher than romance. It means that people prefer to 'a love to get marriage' in Korean modern society, than 'love for love affair'. It seems to be reflection of cognition change, marriage should be based on true love. This study is expected to be applied to the study of trend change through social media.

• The Journal of Korean Academy of Sensory Integration
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• v.17 no.1
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• pp.43-53
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• 2019

Objective : This study was designed to find the latest intervention trends in treatment of children with attention deficit hyperactivity disorder (ADHD) in South Korea. Methods : Studies on ADHD published in Korean journals from January 2004 to December 2018 were reviewed. The databases used were DBpia, Google Scholar, RISS, and KISS. The search terms were "attention deficit hyperactivity," "child," and "intervention." A total of 14 studies were selected. The results of this study were as follows: Patient, Intervention, Comparison, Outcome. Results : The level of evidence was the highest in the single subject study of level IV, and the methodological quality was the most common study. The interventional metronome (IM) intervention was the most frequently used, and the evaluation tools used in the measurement were the Long Form Assessment of the Interactive Metronome and the Korean Behavior Child Checklist. The Korean ADHD interventions showed statistically significant improvement in concentration, hyperactivity, task performance, excessive language use, and timing. Conclusions : Various types of interventions were provided for children with ADHD in South Korea. The interventions showed positive effects, and provided basic data for evidence-based implementation in clinical practice. In the future, a model study should be conducted, to establish an effective service delivery system, as well as ongoing research on children with ADHD.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.237-245
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• 2022

This study examines the social discourse on the characteristics of the learning community in the untact era, and discusses the directions that learning communities for children could explore and consider in the pandemic situation and beyond. For this purpose, big data for one year, from January 20, 2020 to January 20, 2021, were collected through internet portal sites (includingincluding Google News, Daum, Naver and other News surfaces), using two keywords "untact" and "learning community", and analyzed by employing a word frequency and network analysis method. The analysis results show that several important terms, such as 'village education community', 'operation', 'activity', 'corona 19', 'support', and 'online' are closely related to the learning community in the untact era. The findings from this study also have implications for developing the learning community as an alternative model to fill the existing gaps in public care and education for children during the prolonged pandemic and afterwards. In conclusion, the study findings highlight that it is meaningful to identify key terms and concepts through word frequency analysis in order to examine social trends and issues related to the learning community.

• The Journal of Internal Korean Medicine
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• v.44 no.3
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• pp.313-353
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• 2023

Objectives: Heart failure is a chronic disease with increasing prevalence rates despite advancements in medical technology. Korean medicine utilizes herbal prescriptions to treat heart failure, but little is known about the specific herbal medicines comprising the network of herbal prescriptions for heart failure. This study proposes a novel methodology that can efficiently develop prescriptions and facilitate experimental research on heart failure by utilizing existing databases. Methods: Herbal medicine prescriptions for heart failure were identified through a PubMed search and compiled into a Google Sheet database. NetMiner 4 was used for network analysis, and the individual networks were classified according to the herbal medicine classification system to identify trends. K-HERB NETWORK was utilized to derive related prescriptions. Results: Network analysis of heart failure prescriptions and herbal medicines using NetMiner 4 produced 16 individual networks. Uhwangcheongsim-won (牛黃淸心元), Gamiondam-tang (加味溫膽湯), Bangpungtongseong-san (防風通聖散), and Bunsimgi-eum (分心氣飮) were identified as prescriptions with high similarity in the entire network. A total of 16 individual networks utilized K-HERB NETWORK to present prescriptions that were most similar to existing prescriptions. The results provide 1) an indication of existing prescriptions with potential for use to treat heart failure and 2) a basis for developing new prescriptions for heart failure treatment. Conclusion: The proposed methodology presents an efficient approach to developing new heart failure prescriptions and facilitating experimental research. This study highlights the potential of network pharmacology methodology and its possible applications in other diseases. Further studies on network pharmacology methodology are recommended.

• Journal of Distribution Science
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• v.8 no.4
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• pp.5-15
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• 2010

This study investigated research trends of JDS that KODISA published and gave implications to elevate quality of scholarly journals. In other words, the study classified scientific system of distribution area to investigate research trends and to compare it with other scholarly journals of distribution and to give implications for higher level of JDS. KODISA published JDS Vol.1 No.1 for the first time in 1999 followed by Vol.8 No.3 in September 2010 to show 109 theses in total. KODISA investigated subjects, research institutions, number of participants, methodology, frequency of theses in both the Korean language and English, frequency of participation of not only the Koreans but also foreigners and use of references, etc. And, the study investigated JDR of KODIA, JKDM(The Journal of Korean Distribution & Management) and JDA that researched distribution, so that it found out development ways. To investigate research trends of JDS that KODISA publishes, main category was made based on the national science and technology standard classification system of MEST (Ministry Of Education, Science And Technology), table of classification of research areas of NRF(National Research Foundation of Korea), research classification system of both KOREADIMA and KLRA(Korea Logistics Research Association) and distribution science and others that KODISA is looking for, and distribution economy area was divided into general distribution, distribution economy, distribution, distribution information and others, and distribution management was divided into distribution management, marketing, MD and purchasing, consumer behavior and others. The findings were as follow: Firstly, main category occupied 47 theses (43.1%) of distribution economy and 62 theses (56.9%) of distribution management among 109 theses in total. Active research area of distribution economy consisted of 14 theses (12.8%) of distribution information and 9 theses (8.3%) of distribution economy to research distribution as well as distribution information positively every year. The distribution management consisted of 25 theses (22.9%) of distribution management and 20 theses (18.3%) of marketing, These days, research on distribution management, marketing, distribution, distribution information and others is increasing. Secondly, researchers published theses as follow: 55 theses (50.5%) by professor by himself or herself, 12 theses (11.0%) of joint research by professors and businesses, Professors/students published 9 theses (8.3%) followed by 5 theses (4.6%) of researchers, 5 theses (4.6%) of businesses, 4 theses (3.7%) of professors, researchers and businesses and 2 theses (1.8%) of students. Professors published theses less, while businesses, research institutions and graduate school students did more continuously. The number of researchers occupied single researcher (43 theses, 39.5%), two researchers (42 theses, 38.5%) and three researchers or more (24 theses, 22.0%). Thirdly, professors published theses the most at most of areas. Researchers of main category of distribution economy consisted of professors (25 theses, 53.2%), professors and businesses (7 theses, 14.9%), professors and businesses (7 theses, 14.9%), professors and researchers (6 theses, 12.8%) and professors and students (3 theses, 6.3%). And, researchers of main category of distribution management consisted of professors (30 theses, 48.4%), professors and businesses (10 theses, 16.1%), and professors and researchers as well as professors and students (6 theses, 9.7%). Researchers of distribution management consisted of professors, professors and businesses, professors and researchers, researchers and businesses, etc to have various types. Professors mainly researched marketing, MD and purchasing, and consumer behavior, etc to demand active participation of businesses and researchers. Fourthly, research methodology was: Literature research occupied 45 theses (41.3%) the most followed by empirical research based on questionnaire survey (44 theses, 40.4%). General distribution, distribution economy, distribution and distribution management, etc mostly adopted literature research, while marketing did empirical research based on questionnaire survey the most. Fifthly, theses in the Korean language occupied 92.7% (101 theses), while those in English did 7.3% (8 theses). No more than one thesis in English was published until 2006, and 7 theses (11.9%) were published after 2007 to increase. The theses in English were published more to be affirmative. Foreigner researcher published one thesis (0.9%) and both Korean researchers and foreigner researchers jointly published two theses (1.8%) to have very much low participation of foreigner researchers. Sixthly, one thesis of JDS had 27.5 references in average that consisted of 11.1 local references and 16.4 foreign references. And, cited times was 0.4 thesis in average to be low. The distribution economy cited 24.2 references in average (9.4 local references and 14.8 foreign references and JDS had 0.6 cited reference. The distribution management had 30.0 references in average (12.1 local references and 17.9 foreign references) and had 0.3 reference of JDS itself. Seventhly, similar type of scholarly journal had theses in the Korean language and English: JDR( Journal of Distribution Research) of KODIA(Korea Distribution Association) published 92 theses in the Korean language (96.8%) and 3 theses in English (3.2%), that is to say, 95 theses in total. JKDM of KOREADIMA published 132 theses in total that consisted of 93 theses in the Korean language (70.5%) and 39 theses in English (29.5%). Since 2008, JKDM has published scholarly journal in English one time every year. JDS published 52 theses in the Korean language (88.1%) and 7 theses in English (11.9%), that is to say, 59 theses in total. Sixthly, similar type of scholarly journals and research methodology were: JDR's research methodology had 65 empirical researches based on questionnaire survey (68.4%), followed by 17 literature researches (17.9%) and 11 quantitative analyses (11.6%). JKDM made use of various kinds of research methodologies to have 60 questionnaire surveys (45.5%), followed by 40 literature researches (30.3%), 21 quantitative analyses (15.9%), 6 system analyses (4.5%) and 5 case studies (3.8%). And, JDS made use of 30 questionnaire surveys (50.8%), followed by 15 literature researches (25.4%), 7 case studies (11.9%) and 6 quantitative analyses (10.2%). Ninthly, similar types of scholarly journals and Korean researchers and foreigner researchers were: JDR published 93 theses (97.8%) by Korean researchers except for 1 thesis by foreigner researcher and 1 thesis by joint research of the Korean researchers and foreigner researchers. And, JKDM had no foreigner research and 13 theses (9.8%) by joint research of the Korean researchers and foreigner researchers to have more foreigner researchers as well as researchers in foreign countries than similar types of scholarly journals had. And, JDS published 56 theses (94.9%) of the Korean researchers, one thesis (1.7%) of foreigner researcher only, and 2 theses (3.4%) of joint research of both the Koreans and foreigners. Tenthly, similar type of scholarly journals and reference had citation: JDR had 42.5 literatures in average that consisted of 10.9 local literatures (25.7%) and 31.6 foreign literatures (74.3%), and cited times accounted for 1.1 thesis to decrease. JKDM cited 10.5 Korean literatures (36.3%) and 18.4 foreign literatures (63.7%), and number of self-cited literature was no more than 1.1. Number of cited times accounted for 2.9 literatures in 2008 and then decreased continuously since then. JDS cited 26,8 references in average that consisted of 10.9 local references (40.7%) and 15.9 foreign references (59.3%), and number of self-cited accounted for 0.2 reference until 2009, and it increased to be 2.1 references in 2010. The author gives implications based on JDS research trends and investigation on similar type of scholarly journals as follow: Firstly, JDS shall actively invite foreign contributors to prepare for SSCI. Secondly, ratio of theses in English shall increase greatly. Thirdly, various kinds of research methodology shall be accepted to elevate quality of scholarly journals. Fourthly, to increase cited times, Google and other web retrievals shall be reinforced to supply scholarly journals to foreign countries more. Local scholarly journals can be worldwide scholarly journal enough to be acknowledged even in foreign countries by improving the implications above.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.