• Journal of Engineering Education Research
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• v.24 no.1
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• pp.46-52
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• 2021

The purpose of this study is to clarify that critical writing can be a positive stimulus factor for the cultivation of critical thinking through actual cases of writing education targeting engineering students in universities. Critical writing education is a very important way to develop critical thinking necessary for acquiring scientific knowledge, sharing social values, creativity and cultivating new production capacity. Especially, when critical writing education is performed with materials that maintain critical view of social reality such as the movie "Bowling for Columbine", it is characterized by the fact that it is naturally combined with the dimension of engineering ethics faced by engineers from the analysis and judgment of social reality. This is an example of the fact that critical thinking education for engineering students does not necessarily meet their major areas.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.267-269
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• 2019

There are many recommendation systems offer an effort to get better preciseness the information to the users. In order to further improve more accuracy, the social network analysis method which is used to analyze data to community detection in social networks was introduced in the recommendation system and the result shows this method is improving more accuracy. In this paper, we propose a movie recommendation system using social network analysis and normalized discounted cumulative gain with the best accuracy. To estimate the performance, the collaborative filtering using the k nearest neighbor method, the social network analysis with collaborative filtering method and the proposed method are used to evaluate the MovieLens data. The performance outputs show that the proposed method get better the accuracy of the movie recommendation system than any other methods used in this experiment.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.87-102
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• 2009

With the growth of Web 2.0, lots of services allow yours to post their personal information and useful knowledges on networked information spaces such as blogs and online communities etc. As the services are generalized, recent researches related to social network have gained momentum. However, most social network services do not support machine-processable semantic knowledge, so that the information cannot be shared and reused between different domains. Moreover, as explicit definitions of relationships between individual social entities do not be described, it is difficult to analyze social network for inferring unknown semantic relationships. To overcome these limitations, in this paper, we propose a social network analysis system with personal photographic data up-loaded by virtual community users. By using ontology, an informative connectivity between a face entity extracted from photo data and a person entity which already have social relationships was defined clearly and semantic social links were inferred with domain rules. Then the inferred links were provided to yours as a visualized graph. Based on the graph, more efficient social network analysis was achieved in online community.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.243-253
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• 2020

As economic profits and social influences of firms grow with economic development and their organizational expansion, consumers increasingly require firms to have their social responsibility. Because social responsibility strongly influences corporate reliability, consumers' intention to purchase, customer loyalty to the products and the recognition of an ethical firm have gained attention as a concept of strategical importance. The prosperity of society should be proceeded for the sustainable development of a firm and the necessity of social responsibility should be emphasized to achieve virtuous circle structure that promotes growth. Additionally, the social responsibility should be proceeded to form trust on a firm. It is very important to change the recognition of consumers to purchase products and increase the profit of a company. This study aims to analyze how social responsibility properties of firms (economic, ethical, discretionary, and legal aspects as low-level factors of social responsibility which Carroll (1979) defined) affect corporate reliability and purchase intention. The analysis found that consumers trust in firms are positively influenced by ethical responsibility (0.391), economic responsibility (0.293), legal responsibility (0.251), and discretionary responsibility (0.248). The relationship between sub-factor of social responsibility and purchase intention is not significantly influenced by other explanatory variables. Corporate trust exerts a direct influence on purchase Intention (0.456). The social responsibility of a firm didn't influence a direct purchase intention. It was found that it brought positive effect on the purchase intention in the course of forming trust. This study suggests that firms should make efforts to understand the relationship between corporate trust and purchase intention along with the characteristics of social responsibility that consumers recognize and improve management strategies for mutual complementary interests.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.33-39
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• 2018

Social enterprises are companies that provide jobs to the vulnerable and provide social services. However, sustainable management of social enterprises is very difficult in a rapidly changing market environment. Therefore, for the sustainable management of social enterprise, it is assumed that the duty efficiency of the members of the social enterprise is most important in the limited resource environment, and that the social entrepreneur can increase the efficiency of the work by giving delegation to the members. Therefore, this study investigates how social entrepreneurs influence on the job efficiency of members when giving psychological empowerment to members of social enterprise based on social entrepreneurship. When giving empowerment leadership to members, And it has a significant effect on job efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1733-1750
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• 2011

In the early stages of a software project, it is critical to understand the needs of the customers and elicit their customer requirements. Various requirements elicitation methods have been proposed. However, existing methods still have the limitations such as a limited number of target customers, limited expression of customers' opinions, and difficulty in collecting the customers' opinions continuously. A novel method for eliciting customer requirements is proposed by utilizing a social network service (SNS), which is a shared source of raw information of the customers' needs and opinions. The proposed method is validated to show its effectiveness in overcoming the limitations of existing methods.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.4
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• pp.61-75
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• 2007

In ubiquitous computing, shared environments are required to adapt to people intelligently. Based on information about user preferences, the shared environments should be adjusted so that all users in a group are satisfied as possible. Although many group recommender systems have been proposed to obtain this purpose, they only consider average and misery. However, a broad range of philosophical approaches suggest that high inequality reduces social agreeability, and consequently causes users' dissatisfactions. In this paper, we propose social welfare functions, which consider inequalities in users' preferences, as alternative aggregation functions to achieve a social agreeability. Using an example in a previous work[7], we demonstrate the effectiveness of proposed welfare functions as socially agreeable aggregate functions in group recommender systems.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.851-860
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• 2021

The Knowledge Transfer (KT) for higher education institutions (HEIs) is boundless. Still and all, the members of the staff affiliated with these institutions do recognize an array of hitches in relation to KT practices. The study in question underscores social interactions, training, and Information and Communication Technology (ICT) as the primary barriers and treats them as the independent variables of the study. The study posits that inadequate management of the above-mentioned barriers would impact effective KT unfavorably. Besides, putting forth some striking solutions needed to fix the obstructions that hamper the adequate management of the KT exercises is another aim of the study. For data collection purposes, the study picks out higher education institutions (public) of the Quetta district. The reckoned sample size is 317 subjects. The research type that has been used is cross-sectional research and, in this context, the cross-sectional explanatory sequential design has been used. Concerning the findings of the paper, the results of PLS-SEM show positive and significant relationships of social interaction and training with knowledge transfer, while ICT shows an insignificant positive relationship with the knowledge transfer. The most influencing factor for the knowledge transfer is social interaction as suggested by social interaction theory.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.538-547
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• 2013

In this paper, we propose a bias detection method that is based on personal and social opinions that express contrasting views on competing topics on Twitter. We used unsupervised polarity classification is conducted for learning social opinions on targets. The $tf{\cdot}idf$ algorithm is applied to extract targets to reflect sentiments and features of tweets. Our method addresses there being a lack of a sentiment lexicon when learning social opinions. To evaluate the effectiveness of our method, experiments were conducted on four issues using Twitter test collection. The proposed method achieved significant improvements over the baselines.

• Journal of the Korea Society of Computer and Information
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• v.22 no.5
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• pp.73-79
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• 2017

In this paper, we propose a design and implementation of a DB system for providing comprehensive information retrieval service about social economic information. We classify social economic organizations into 6 major categories and 35 small categories. The DB contains 25,938 social economic organizations in total. The DB system provides simple and intuitive interface for searching information such as keyword search, category search and initial search. Fully loaded time of webpage of implemented DB system achieved 2.3s by Vancouver, Canada Server.