• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.53-68
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• 2015

This study analyzed online word-of-mouth information using content analysis to help practical categorization of two-sided eWOM. A total of 402 online consumer reviews on search goods and experience goods were collected. Descriptive characteristics(information direction, length of review line) and content structural characteristics(product benefit types, information presentation methods) were used as analysis criteria. The study results are as follows. First, the types of two-sided e-WOM direction were made of positive/negative, negative/positive, positive/negative/ positive, and negative/positive/negative. Second, the length of two-sided eWOM was longer than the length of one-sided eWOM and blended type accounted for the highest proportion both one-sided and two-sided eWOM at the aspect of product benefit. Third, holistic presentation method was overwhelmingly high in one-sided eWOM, whereas blended and analytic presentation methods were somewhat high in two-sided eWOM. Fourth, holistic presentation method was high in search goods, whereas blended and analytic presentation methods were high in experience goods. Based on these results, implications for two-sided e-WOM study and further research issues were discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.632-638
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• 2009

Probabilistic Latent Semantic Analysis has many applications in information retrieval and filtering, natural language processing, machine learning from text, and in related areas. In this paper, we propose an algorithm using weighted Probabilistic Latent Semantic Analysis Model to find the contextual phrases and opinions from documents. The traditional keyword search is unable to find the semantic relations of phrases, Overcoming these obstacles requires the development of techniques for automatically classifying semantic relations of phrases. Through experiments, we show that the proposed algorithm works well to discover semantic relations of phrases and presents the semantic relations of phrases to the vector-space model. The proposed algorithm is able to perform a variety of analyses, including such as document classification, online reputation, and collaborative recommendation.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.328-331
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• 2013

Incentive/Disincentive (I/D) contracting experiences in many states have been evaluated in terms of time and cost performance and substantial project time savings were found in many project cases. However, there is little understanding on individual project success factors for I/D projects during construction. This paper explores the significance of I/D clause in the success of the MacArthur Maze reconstruction project and summarizes a list of group causes that explains and elaborates on the detailed factors. The methods used for carrying out this study started with a search of online media and news reports and contract documents were also obtained from Caltrans. After review of the preliminary information, Interviews were performed with the Caltrans Resident Engineer and the contractor's project manager who were in charge of the MacArthur Maze reconstruction. In conclusion, the evaluation of their responses hinted at six significant cause groups responsible for the project's success. These groups can be listed as: 1) Motivation, 2) Policy, 3) Teamwork, 4) Communication, 5) Expectation, and 6) Resource Management.

• Journal of Animal Science and Technology
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• v.49 no.2
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• pp.183-194
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• 2007

We examined the expression patterns of the chicken TCs(tentative consensus sequences) originated from GermOnline genes in various chicken tissues, applying information from GermOnline to chicken organisms. 42 TCs among 84 chicken homologous TCs from the pool of 84 genes related to germ cell lineage in mouse(10), rat(71) and human(3) had high homology based on a BLAST search. Of these, Hmgcs2 and Sycp3 was shown to be expressed in a testis- specific manner and a reproductive organ(testis and ovary)-specific manner, respectively, by RT- PCR analysis. Crmp4, Cyct, Ldhc, Epha7, Pcsk4 and Dnmt3a are expressed in brain, testis, and ovary. The characterization of chicken genes originated from GermOnline in this research may give an enormously useful source of information related to germ cell development.

• Korean journal of communication and information
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• v.45
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• pp.463-495
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• 2009

Korea has started to pay attention to civic journalism in recent years while it initially emerged in the United State since late 1980s. Furthermore, albeit some discernable limitations, the Internet has played an important role in fertilizing civic journalism as indicated by the emergence of online news media and the increasing number of civic journalists engaged in the online activities. Whereas there are some patterns of civic journalism practice and the civic influence commonly observed in both countries, there are significant factors that distinguish th1e case of Korea from that of the U.S. The purpose of this study is to compare the two countries in terms of the patterns of civic journalism practice and civic influence. This goal has been achieved by analyzing ‘CNN iReport’ in the U.S. and ‘Ohmynews’ in Korea, both of which are prime civic journalism websites. Those websites have been compared in light of four standards of civic journalism: first, the degree of post-objectivism; second, the search for effective resolutions of social problems; third, civic engagement in the news making process to enhance bottom-up agenda setting; and finally, citizens’ interaction with the news. The results reveal that the American civic journalism website is more likely to shed light on deviating from the principle of objectivity and seeking alternatives and resolutions of social problems. Moreover, it effectively utilizes civic engagement in the news Abstracts 551 making process as indicated by the higher numbers of civic journalists and civic news resources. Also, readers’ interaction with the news was found to be more active in the iReport website than in the Ohmynews.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.4
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• pp.5-24
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• 2021

The purpose of this study was to investigate and analyze the operating conditions of lecture contents in contactless online classes for University students. First, as a result of analyzing the responses of 93 respondents, 93.3% of the respondents took real-time online lectures (47.7%) or recorded video lectures (45.6%). Second, as a result of analyzing the contents used as textbooks, it was found that e-books (materials) and paper books (materials) were used together (36.6%), or e-books or electronic materials (36.6% and 37.6% respectively) were used in both liberal arts (47.3%) and major subjects (39.8%). In addition to textbooks, both major subjects and liberal arts highly used web materials (47.6% and 40.5% respectively) and YouTube materials (33.3% and 48.0% respectively) as external materials. Third, both liberal arts and major subjects used 'electronic files in the form of PPT or text organized and written by instructors' (62.9% and 58.1% respectively), 'internet materials' (16.7% and 19% respectively) and 'paper book or materials' (10.4% and 12.3% respectively) to share lecture contents. For the screen displayed lecture contents, 93.5% of the respondents satisfied in major subjects, and 90.2% of the respondents satisfied in liberal arts. These results suggest developing multimedia-based lecture contents and an evaluation solution capable of real-time exam supervision, developing a task management system capable of AI-based plagiarism search, task guidance, and task evaluation, and institutionalizing a solution to copyright problems for electronicizing lecture materials so that lectures can be given in the ubiquitous environment.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.690-701
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• 2013

With the increasing adoption of social network services (SNS), the cultural and art industry is also embracing SNS as an important tool of marketing. Users can share various cultural experiences on SNS easily, and companies can analyze SNS to understand the users for effective marketing. Based on this background, this study analyzed users' behavior and attitude about movies according to SNS usage types. Users of SNS were surveyed and clustered into 'information seekers', 'fun seekers', and 'relationship seekers'. Next, the behavior of the users in each cluster was compared regarding information search about movies, preferred online advertisement channels, and post-watching behavior. The results showed that the SNS usage type has significant relationship with the behavior and attitude about movies. This suggests that movie industry can establish effective online marketing strategy by analyzing SNS usage of users.

• 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 Digital Convergence
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• v.15 no.7
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• pp.27-39
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• 2017

To grasp the current status of smart campus and look for future directions, this study investigated the usage rate and perceived usefulness of digital devices and services by conducting online survey of 580 university students. The main results are as follows. First, smartphones have the highest ownership rate, followed by laptops, desktops, and digital cameras. Purchase intention of virtual reality devices is highest followed by smart watches/bands, and tablets. Second, mobilization in campus life is almost realized, however the usage of desktops is still high in education and administration context. Digital devices have been perceived particularly useful when searching and sharing information. Third, students use digital services such as search engines, messengers, and online libraries in their learning, and they use messengers, music and video services in their lives. Service usage rate and perceived usefulness are not proportional.