• 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.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.569-578
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• 2021

Thanks to web development today, we can easily access online news via various media. As much as it is easy to access online news, we often face fake news pretending to be true. As fake news items have become a global problem, fact-checking services are provided domestically, too. However, these are based on expert-based manual detection, and research to provide technologies that automate the detection of fake news is being actively conducted. As for the existing research, detection is made available based on contextual characteristics of an article and the comparison of a title and the main article. However, there is a limit to such an attempt making detection difficult when manipulation precision has become high. Therefore, this study suggests using a verifying article to decide whether a news item is genuine or not to be affected by article manipulation. Also, to improve the precision of fake news detection, the study added a process to summarize a subject article and a verifying article through the summarization model. In order to verify the suggested algorithm, this study conducted verification for summarization method of documents, verification for search method of verification articles, and verification for the precision of fake news detection in the finally suggested algorithm. The algorithm suggested in this study can be helpful to identify the truth of an article before it is applied to media sources and made available online via various media sources.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.29 no.3
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• pp.122-128
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• 2018

Objectives: This study evaluated the psychometric properties of the Korean version of the attention-deficit/hyperactivity disorder (ADHD) Stigma Questionnaire (ASQ) and the effect of the source of information about mental health on ADHD stigma. Methods: The Korean translation of the ASQ was prepared, and 673 participants, 20-64 years of age, completed the questionnaire using an online panel survey in South Korea. The participants also completed questionnaires detailing sociodemographic variables and the source of their mental health knowledge. Cronbach's alpha coefficient was used to explore the internal consistency of the ASQ. Factor analysis using Varimax rotation was conducted to investigate the structure of the ASQ. Results: The 26-item ASQ demonstrated excellent internal consistency (Cronbach's alpha=0.940). Factor analysis supported a three-factor structure, including Concerns with Public Attitudes, Negative Self-Image, and Disclosure Concerns. There were no significant differences in the total ASQ scores according to sociodemographic characteristics. Participants who reported the internet as their major source of information about mental health showed higher ASQ scores compared to those who used other sources for mental health information. Conclusion: The Korean translation of the ASQ has acceptable psychometric properties among Korean adults. Inaccurate information from the internet could increase the stigma toward ADHD.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.632-644
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• 2019

The remote monitoring and warning system for dangerous chemicals is designed with the concept of the Cyber-Physical System (CPS) in this paper. The real-time perception, dynamic control, and information service of major hazards chemicals are realized in this CPS system. The CPS system architecture, the physical layer and the applacation layer, are designed in this paper. The terminal node is mainly composed of the field collectors which complete the data acquisition of sensors and video in the physical layers, and the use of application layer makes CPS system safer and more reliable to monitor the hazardous chemicals. The cloud application layer completes the risk identification and the prediction of the major hazard sources. The early intelligent warning of the major dangerous chemicals is realized and the security risk images are given in the cloud application layer. With the CPS technology, the remote network of hazardous chemicals has been completed, and a major hazard monitoring and accident warning online system is formed. Through the experiment of the terminal node, it can be proved that the terminal node can complete the mass data collection and classify. With this experiment it can be obtained the CPS system is safe and effective. In order to verify feasible, the multi-risk warning based on CPS is simulated, and results show that the system solves the problem of hazardous chemicals enterprises safety management.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1238-1249
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• 2020

Throughout the world, aging populations and doctor shortages have helped drive the increasing demand for smart healthcare systems. Recently, these systems have benefited from the evolution of the Internet of Things (IoT), big data, and machine learning. However, these advances result in the generation of large amounts of data, making healthcare data analysis a major issue. These data have a number of complex properties such as high-dimensionality, irregularity, and sparsity, which makes efficient processing difficult to implement. These challenges are met by big data analytics. In this paper, we propose an innovative analytic framework for big healthcare data that are collected either from IoT wearable devices or from archived patient medical images. The proposed method would efficiently address the data heterogeneity problem using middleware between heterogeneous data sources and MapReduce Hadoop clusters. Furthermore, the proposed framework enables the use of both fog computing and cloud platforms to handle the problems faced through online and offline data processing, data storage, and data classification. Additionally, it guarantees robust and secure knowledge of patient medical data.

• International Journal of Costume and Fashion
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• v.10 no.1
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• pp.81-91
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• 2010

The purpose of this study was to investigate differences in purchase behaviors for school uniforms among adolescent consumer groups which were segmented by the type of retailer they patronized. An online survey was carried out and 907 data sets were analyzed using SPSS. The results support that classifying adolescent consumers according to what type of retailers they patronize lead to a proper understanding of the segmentation of the school uniform market. The adolescent consumers consisted of five groups categorized by the retailer types. These types included special stores, department stores, discount stores, small custom-made stores and stores designated by schools. The results also indicated that consumer groups segmented by retailer patronage differ significantly in their use of multimedia information sources. Five consumer groups showed significant differences in two purchase evaluative criteria: utilities and promotions.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7847-7852
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• 2015

Purpose: Research carried out with gynecologic cancer patients using CAM was reviewed to provide a source for discussing which CAM method is used for which purpose, patients' perceptions on the effects/side effects occurred during/after using CAM and their sources of information regarding CAM. Materials and Methods: This literature review was carried out for the period between January 2000 and March 2015 using Scopus, Dynamed, Med-Line, Science Dırect, Ulakbim, Research Starters, Ebscohost, Cinahl Complete, Academic Onefile, Directory of Open Access Journals, BMJ Online Journals (2007-2009), Ovid, Oxford Journal, Proquest Hospital Collection, Springer-Kluwer Link, Taylor & Francis, Up To Date, Web Of Science (Citation Index), Wiley Cochrane-Evidence Base, Wiley Online Library, and Pub-Med search databases with "complementary and alternative medicine, gynecologic cancer" as keywords. After searching through these results, a total of 12 full length papers in English were included. Results: CAM use in gynecologic cancer patients was discussed in 8 studies and CAM use in breast and gynecologic cancer patients in 4. It was determined that the frequency of CAM use varies between 40.3% and 94.7%. As the CAM method, herbal medicines, vitamins/minerals were used most frequently in 8 of the studies. When the reasons why gynecologic cancer patients use CAM are examined, it is determined that they generally use to strengthen the immune system, reduce the side effects of cancer treatment and for physical and psychological relaxation. In this review, most of the gynecologic cancer patients perceived use of CAM as beneficial. Conclusions: In order that the patients obtain adequate reliable information about CAM and avoid practices which may harm the efficiency of medical treatment, it is recommended that "Healthcare Professionals" develop a common language.

• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.99-123
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• 2004

Traditionally. theses and dissertations have been extremely underutilized information sources due to their lack of physical availability. The development of electronic theses and dissertations system will provide the opportunity for theses and dissertations to be recognized as a basic channel for the dissemination of research findings and an essential resource in the discovery process. In digital environment. many universities and libraries throughout the world are now making digitized versions of traditional(print) dissertations available online. The purpose of this paper is to analyze the current theses and dissertations management system based on web questionaries and survey of home pages. and to suggest a standardized theses and dissertation management model in Korea.

• Fashion, Industry and Education
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• v.16 no.1
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• pp.36-45
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• 2018

Recently China has become one of the major markets for luxury brands. In addition, practicing social responsibility by manufacturers of luxury brands has become ubiquitous because consumers' perception of such practices may affect their purchase decisions positively. This study explored Chinese shoppers' perception of luxury brands' social responsibility practices and their information seeking behavior. In this study, value congruence was used as a theoretical framework. Twelve participants were selected out of customers in a shopping mall in Beijing, and they were subject to in-depth interview. The interview consisted of open-ended questions about perception of luxury brands' social responsibility practices, sources to access such practices, and the degree of personal value congruence to such practices as well as demographic information. Qualitative approach was used to analyze the data. Half of the participants indicated their awareness of the social responsibility practices of luxury brands, which sets up a foundation for understanding importance of luxury brands' social responsibility practices. Approximately half of the participants preferred to learn about luxury brands' socially responsible practices online especially via social media. These findings imply that Chinese luxury shoppers' trust and preference for the companies would be enhanced by effective development and advertisement of companies' social responsibility practices, and thus provide luxury companies with useful information on marketing strategies.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.13-31
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• 2016

Despite expectations of short- or long-term positive effects of corporate social responsibility (CSR) on firm performance, the results of existing research into this relationship are inconsistent partly due to lack of clarity about subordinate CSR concepts. In this study, keywords related to CSR concepts are extracted from atypical sources, such as newspapers, using text mining techniques to examine the relationship between CSR and firm performance. The analysis is based on data from the New York Times, a major news publication, and Google Scholar. We used text analytics to process unstructured data collected from open online documents to explore the effects of CSR on short- and long-term firm performance. The results suggest that the CSR index computed using the proposed text - online media - analytics predicts long-term performance very well compared to short-term performance in the absence of any internal firm reports or CSR institute reports. Our study demonstrates the text analytics are useful for evaluating CSR performance with respect to convenience and cost effectiveness.