• Review of Culture and Economy
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• v.21 no.2
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• pp.197-229
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• 2018

This study investigates the social discourse for Korean women's leisure culture and analyzes the conflicts between the ideologies which affected to the women's leisure issues with the social and cultural context. For this purpose, this study analyzed a sum of 652,513 words of 4,614 news articles about Korean women's leisure by applying semantic network analysis. In the 1960s, both the enthusiasm for 'modernization' and 'good wife and wise mother' ideologies were simultaneously affected to women's leisure discourse. 'The good wife and wise mother' ideology have a stronger impact on women's leisure culture in the 1970s. In the 1980s, even though the Korean women had higher education background and advanced social status compared to the former periods, both 'good wife and wise mother' ideology and 'modern career women' ideology conflicted each other. The conflicts between the two ideologies were intensified in the 1990s and the women tended to sacrifice their leisure in the course of the ideological conflicts in the 2000s. In the 2010s, women who exhausted due to the intensified conflicts between the two ideologies showed preference for passive forms of leisure.

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.364-371
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• 2019

The World Health Organization (WHO) announced the 11th International Classification System (ICD-11), which classifies game addiction as a disease in 2018. Sin stocks are defined as the companies that have negative addictive properties and are taxed on social costs. If a game disorder is listed in the disease classification system in Korea, it is highly likely that Korean game companies may be considered as sin stocks that causes negative addictive properties and social costs such as the game addiction and the game addiction tax. This suggests that game companies could be newly included in the scope of sin stocks in Korea. In this study, we examine the effect of the inclusion of game companies in the scope of sin stocks on the job preferences of game companies. We found that there is a high level of opposition to the opinion of the listing sin stocks of game companies, and a high degree of addiction and gambling was suggested as the cause of the game companies being classified as sin stocks. We also found that firm value and job preference would be decrease if a game company was classified as sin stocks. The study is meaningful in that it suggests that game companies can be perceived negatively as sin stocks due to the disease code of game disorder, which has recently emerged as a social issue. Also, this study will contribute to the academia and market participants by reporting statistically the effect of the classification of sin stocks in game companies on job preferences for game companies.

• Journal of Science Education
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• v.47 no.1
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• pp.63-74
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• 2023

This study aims to investigate the effects of pre-service elementary teachers' scientific self-efficacy by science motivation according to the academic track in high school. The subjects of this study were 525 pre-service elementary teachers of which 350 pre-service elementary teachers were selected from the humanities and social sciences track in high school and 175 pre-service elementary teachers were selected from the science-engineering track in high school. In order to investigate the difference between scientific self-efficacy and science motivation among pre-service elementary teachers, Independent sample t-test and Cohen's d were done. In order to find out about the Influencing of scientific self-efficacy on science motivation, multiple regression analysis was used. The results of this study were as follows: First, there were statistically significant differences in scientific self-efficacy and science motivation, and the average of pre-service elementary teachers who selected science-engineering were significantly higher. Second, explanation power of scientific self-efficacy on science motivation appeared as 66.7~68.3%. The explanatory power of pre-service elementary teachers' who selected humanities and social sciences were higher. The relative importance was high in task difficulty preference factor to humanities and social sciences, was high in self-regulation efficacy to science-engineering. In conclusion, in order for pre-service elementary teachers to achieve high achievement and motivation in science subjects, and to teach science well to students in the school field, teacher education that can improve scientific self-efficacy should be conducted.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.53-77
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• 2015

Korea has witnessed an increasing number of domestic patent applications, but a majority of them are not utilized to their maximum potential but end up becoming obsolete. According to the 2012 National Congress' Inspection of Administration, about 73% of patents possessed by universities and public-funded research institutions failed to lead to creating social values, but remain latent. One of the main problem of this issue is that patent creators such as individual researcher, university, or research institution lack abilities to commercialize their patents into viable businesses with those enterprises that are in need of them. Also, for enterprises side, it is hard to find the appropriate patents by searching keywords on all such occasions. This system proposes a patent recommendation system that can identify and recommend intellectual rights appropriate to users' interested fields among a rapidly accumulating number of patent assets in a more easy and efficient manner. The proposed system extracts core contents and technology sectors from the existing pool of patents, and combines it with secondary social knowledge, which derives from tags information created by users, in order to find the best patents recommended for users. That is to say, in an early stage where there is no accumulated tag information, the recommendation is done by utilizing content characteristics, which are identified through an analysis of key words contained in such parameters as 'Title of Invention' and 'Claim' among the various patent attributes. In order to do this, the suggested system extracts only nouns from patents and assigns a weight to each noun according to the importance of it in all patents by performing TF-IDF analysis. After that, it finds patents which have similar weights with preferred patents by a user. In this paper, this similarity is called a "Domain Similarity". Next, the suggested system extract technology sector's characteristics from patent document by analyzing the international technology classification code (International Patent Classification, IPC). Every patents have more than one IPC, and each user can attach more than one tag to the patents they like. Thus, each user has a set of IPC codes included in tagged patents. The suggested system manages this IPC set to analyze technology preference of each user and find the well-fitted patents for them. In order to do this, the suggeted system calcuates a 'Technology_Similarity' between a set of IPC codes and IPC codes contained in all other patents. After that, when the tag information of multiple users are accumulated, the system expands the recommendations in consideration of other users' social tag information relating to the patent that is tagged by a concerned user. The similarity between tag information of perferred 'patents by user and other patents are called a 'Social Simialrity' in this paper. Lastly, a 'Total Similarity' are calculated by adding these three differenent similarites and patents having the highest 'Total Similarity' are recommended to each user. The suggested system are applied to a total of 1,638 korean patents obtained from the Korea Industrial Property Rights Information Service (KIPRIS) run by the Korea Intellectual Property Office. However, since this original dataset does not include tag information, we create virtual tag information and utilized this to construct the semi-virtual dataset. The proposed recommendation algorithm was implemented with JAVA, a computer programming language, and a prototype graphic user interface was also designed for this study. As the proposed system did not have dependent variables and uses virtual data, it is impossible to verify the recommendation system with a statistical method. Therefore, the study uses a scenario test method to verify the operational feasibility and recommendation effectiveness of the system. The results of this study are expected to improve the possibility of matching promising patents with the best suitable businesses. It is assumed that users' experiential knowledge can be accumulated, managed, and utilized in the As-Is patent system, which currently only manages standardized patent information.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.147-159
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• 2021

After the 2020 Corona 19 pandemic, consumers' online consumption is increasing rapidly, and non-store online retail channels are showing high growth. In particular, social media is gaining its status as a social media market where direct transactions take place in the means of promoting companies' brands and products. In this study, changes in consumer behavior after the Corona 19 pandemic are different in choosing online shopping media such as existing online shopping malls and SNS markets that can be classified into open social media and closed social media when purchasing agri-food online. We tried to find out what type of product is preferred in the selection of agri-food products. For this study, demographic characteristics of consumers, perceived risk of consumers, and dietary lifestyle were set as independent variables to investigate the effect on online shopping media type and product selection. The summary of the empirical analysis results is as follows. When consumers purchase agri-food online, there are significant differences in demographic characteristics, consumer perception risks, and detailed factors of dietary lifestyle in selecting shopping channels such as online shopping malls, open social media, and closed social media. Appeared to be. The consumers who choose the open SNS market are higher in men than in women, with lower household income, and higher in consumers seeking health and taste. Consumers who choose the closed SNS market were analyzed as consumers who live in rural areas and have a high degree of risk perception for delivery. Consumers who choose existing online shopping malls have high educational background, high personal income, and high consumers seeking taste and economy. Through this study, we tried to provide practical assistance by providing a basis for judgment to farmers who have difficulty in selecting an online shopping medium suitable for their product characteristics. As a shopping channel for agri-food, social media is not a simple promotional channel, but a direct transaction. It can be differentiated from existing studies in that it is approached as a market that arises.

• Biomolecules & Therapeutics
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• v.22 no.4
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• pp.363-369
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• 2014

Synthetic cannabinoids (CBs) such as the JWH series have caused social problems concerning their abuse liability. Because the JWH series produces euphoric and hallucinogenic effects, they have been distributed illegally under street names such as "Spice" and "Smoke". Many countries including Korea have started to schedule some of the JWH series compounds as controlled substances, but there are a number of JWH series chemicals that remain uncontrolled by law. In this study, three synthetic CBs with different binding affinities to the $CB_1$ receptor (JWH-073, 081, and 210) and ${\Delta}^9$-tetrahydrocannabinol (${\Delta}^9$-THC) were evaluated for their potential for psychological dependence. The conditioned place preference test (unbiased method) and self-administration test (fixed ratio of 1) using rodents were conducted. $K_i$ values of the three synthetic cannabinoids were calculated as supplementary data using a receptor binding assay and overexpressed $CB_1$ protein membranes to compare dependence potential with $CB_1$ receptor binding affinity. All mice administered JWH-073, 081, or 210 showed significantly increased time spent at unpreferred space in a dose-dependence manner in the conditioned place preference test. In contrast, all tested substances except ${\Delta}^9$-THC showed aversion phenomenon at high doses in the conditioned place preference test. The order of affinity to the $CB_1$ receptor in the receptor binding assay was JWH-210 > JWH-081 >> JWH-073, which was in agreement with the results from the conditioned place preference test. However, no change in self-administration was observed. These findings suggest the possibility to predict dependence potential of synthetic CBs through a receptor binding assay at the screening level.

• Journal of Nutrition and Health
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• v.41 no.1
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• pp.77-88
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• 2008

This research was carried out a to investigate the food habit and preference of parents' social and economic level with 681 children (145 of Kindergarten, 300 of Children, 236 of Adolescences) in Seoul and Gyeonggi area using question naires. The parents' income level divided into 2 groups, less than 4 million won and equal or greater than 4 million won. Most of the middle years were over-weighing but kindergarten and adolescences had standard weights. The majority of parents had Bachelor degrees, most of father were office workers, majority of mothers of kindergarten with parents' income level less than 4 million won were professional women and mothers of the rest of the groups were mostly house wives. The middle years with parents income level less than 4 million son were skipping meals most frequently, but other groups didn't show much differences in their eating habits. All age groups showed that they like meats the most and dislike vegetables the worst. All age groups also showed that they mostly eat out 1-2 times a week and the next was 3-4 times a week. All age groups preferred ice creams, fruits, juices and snacks for their desserts. The middle years with parents' income equal or greater than 4 million won also showed high preference on strawberry and chocolate flavored milk, burgers and pizzas. The food s that preferred to eat when dining out were Chinese foods (Ja-jang-myeon and sweet and sour pork) for kindergarten group, Korean foods (kalbi and bulgogi) for the middle years with parents' income level less than 4 million won, family restaurant food (steak and rib) for the middle years with parents' income level equal or greater than 4 million won and Korean foods (kalbi and bulgogi) for the adolescences. The preferred cooking methods were roast (fish and sea weeds) for the kindergarten, roasted meat for the middle years, Kimchi and bean paste pot stew for the adolescences with parents' income level less than 4 million won and roasted meats for the adolescences with parents' income level equal or greater than 4 million won. The results showed that the adolescences with higher parental income lever preferred meats.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.145-162
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• 2008

One of the big concerns in e-society is privacy issue. In special, in developing robust ubiquitous smart space and corresponding services, user profile and preference are collected by the service providers. Privacy issue would be more critical in context-aware services simply because most of the context data themselves are private information: user's current location, current schedule, friends nearby and even her/his health data. To realize the potential of ubiquitous smart space, the systems embedded in the space should corporate personal privacy preferences. When the users invoke a set of services, they are asked to allow the service providers or smart space to make use of personal information which is related to privacy concerns. For this reason, the users unhappily provide the personal information or even deny to get served. On the other side, service provider needs personal information as rich as possible with minimal personal information to discern royal and trustworthy customers and those who are not. It would be desirable to enlarge the allowable personal information complying with the service provider's request, whereas minimizing service provider's requiring personal information which is not allowed to be submitted and user's submitting information which is of no value to the service provider. In special, if any personal information required by the service provider is not allowed, service will not be provided to the user. P3P (Platform for Privacy Preferences) has been regarded as one of the promising alternatives to preserve the personal information in the course of electronic transactions. However, P3P mainly focuses on preserving the buyers' personal information. From time to time, the service provider's business data should be protected from the unintended usage from the buyers. Moreover, even though the user's privacy preference could depend on the context happened to the user, legacy P3P does not handle the contextual change of privacy preferences. Hence, the purpose of this paper is to propose a mutual P3P-based negotiation mechanism. To do so, service provider's privacy concern is considered as well as the users'. User's privacy policy on the service provider's information also should be informed to the service providers before the service begins. Second, privacy policy is contextually designed according to the user's current context because the nomadic user's privacy concern structure may be altered contextually. Hence, the methodology includes mutual privacy policy and personalization. Overall framework of the mechanism and new code of ethics is described in section 2. Pervasive platform for mutual P3P considers user type and context field, which involves current activity, location, social context, objects nearby and physical environments. Our mutual P3P includes the privacy preference not only for the buyers but also the sellers, that is, service providers. Negotiation methodology for mutual P3P is proposed in section 3. Based on the fact that privacy concern occurs when there are needs for information access and at the same time those for information hiding. Our mechanism was implemented based on an actual shopping mall to increase the feasibility of the idea proposed in this paper. A shopping service is assumed as a context-aware service, and data groups for the service are enumerated. The privacy policy for each data group is represented as APPEL format. To examine the performance of the example service, in section 4, simulation approach is adopted in this paper. For the simulation, five data elements are considered: $\cdot$ UserID $\cdot$ User preference $\cdot$ Phone number $\cdot$ Home address $\cdot$ Product information $\cdot$ Service profile. For the negotiation, reputation is selected as a strategic value. Then the following cases are compared: $\cdot$ Legacy P3P is considered $\cdot$ Mutual P3P is considered without strategic value $\cdot$ Mutual P3P is considered with strategic value. The simulation results show that mutual P3P outperforms legacy P3P. Moreover, we could conclude that when mutual P3P is considered with strategic value, performance was better than that of mutual P3P is considered without strategic value in terms of service safety.

• Journal of Science Education
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• v.47 no.2
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• pp.180-191
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• 2023

The purpose of this study was to investigate the preferred SSI topics of students and teachers in elementary, middle, and high schools. It analyzed the similarity of students' and teachers' preferred SSI topics by school level using the cosine similarity measure. A total of 566 students and 327 teachers from elementary, middle, and high schools participated in the study. Sixty topics were identified and listed in the areas of environment, science and technology, health and medicine, and other social issues based on the literature and SSI programs. Students and teachers were asked to select five of their favorite topics. The data was collected online using SurveyMonkey. The collected data was divided into six groups of students and teachers, and the frequency of topic selection was analyzed within each group. The topic preference similarity was analyzed by calculating vector values based on the frequency of the selected topics and measuring the cosine similarity between students, teachers, and teachers and students by school level. The results are as follows: First, the cosine similarity of SSI Preferred Topics between students' school-level cohorts was higher between middle and high school students (0.982) than between elementary and middle school students (0.651) or between elementary and high school students (0.662). Second, the cosine similarity of SSI Preferred Topics between teachers' school-level cohorts was similar for all comparison groups between elementary, middle, and high school. Third, the SSI topic preference similarity between students and teachers by school level had a higher cosine similarity between the elementary student and teacher cohorts (0.974) than the other school level comparisons, middle school (0.621) or high school (0.645). Access to topics of interest to students in SSI education is strongly associated with motivation and persistence in learning, as well as an enjoyable learning experience and positive attitudes toward learning. Therefore, when designing SSI lessons, it is important to examine topics from the perspective of student interest, especially if the teacher has selected SSI topics that are different from students' preferences. Careful instructional design will be needed to overcome the gap.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.