• Journal of Engineering Education Research
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• v.22 no.6
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• pp.64-73
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• 2019

The purpose of this study is to explore characteristics of engineering students' Interpersonal Problems, Emotional Clarity, and Empathic Ability compared with humanities and social sciences students. A total of 739 college students participated in the study (459 enginerring students and 280 humanities and social sciences students). We tested research question by employing the t-test. The result showed that engineering students have higher level of clarity of feelings, perspective taking, empathic concern and lower level of attention to feelings, personal distress than humanities and social sciences students. Moreover, engineering students showed lower level of cold, socially avoidant, exploitable problems than humanities and social sciences students. We dicussed that programs aiming at developing engineering students' emotional awareness and improving their interpersonal relationships should be provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1570-1594
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• 2017

Social network services have recently changed from environments for simply building connections among users to open platforms for generating and sharing various forms of information. Existing user reputation computation methods are inadequate for determining the trust in users on social media where explicit ratings are rare, because they determine the trust in users based on user profile, explicit relations, and explicit ratings. To solve this limitation of previous research, we propose a user reputation computation method suitable for the social media environment by incorporating implicit as well as explicit ratings. Reliable user reputation is estimated by identifying malicious information raters, modifying explicit ratings, and applying them to user reputation scores. The proposed method incorporates implicit ratings into user reputation estimation by differentiating positive and negative implicit ratings. Moreover, the method generates user reputation scores for individual categories to determine a given user's expertise, and incorporates the number of users who participated in rating to determine a given user's influence. This allows reputation scores to be generated also for users who have received no explicit ratings, and, thereby, is more suitable for social media. In addition, based on the user reputation scores, malicious information providers can be identified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.355-370
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• 2014

Cooperative spectrum sensing has been considered as a promising approach to improve the sensing performance in distributed cognitive radio networks. However, there may exist some selfish secondary users (SUs) who are unwilling to cooperate. The presence of selfish SUs could cause catastrophic damage to the performance of cooperative spectrum sensing. Following the social perspective, we propose a Social Tie-based Incentive Scheme (STIS) to deal with the selfish problem for cooperative spectrum sensing in distributed cognitive radio networks. This scheme inspires SUs to contribute sensing information for the SUs who have social tie but not others, and such willingness varies with the strength of social tie value. The evaluation of each SU's social tie derives from its contribution for others. Finally, simulation results validate the effectiveness of the proposed scheme.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.62-69
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• 2012

This thesis proposes a new social network simulator, which can be used for the social network analysis (SNA). It is composed of three modules; initialization, network evolution, and output generation. For the network evolution module, we suggest a modified JGN (MJGN) based on JGN, the network evolution model developed by Jin, Girvan, and Newman. Arena, one of the most popular simulation tools, was used to model the agent based social network simulator. Lastly, some test results were presented to show the value of the proposed simulator when one performs SNA at the longitudinal point of view.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3798-3814
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• 2022

Social recommendation algorithm can alleviate data sparsity and cold start problems in recommendation system by integrated social information. Among them, matrix-based decomposition algorithms are the most widely used and studied. Such algorithms use dot product operations to calculate the similarity between users and items, which ignores user's potential preferences, reduces algorithms' recommendation accuracy. This deficiency can be avoided by a metric learning-based social recommendation algorithm, which learns the distance between user embedding vectors and item embedding vectors instead of vector dot-product operations. However, previous works provide no theoretical explanation for its plausibility. Moreover, most works focus on the indirect impact of social friends on user's preferences, ignoring the direct impact on user's rating preferences, which is the influence of user rating preferences. To solve these problems, this study proposes a user bias drift social recommendation algorithm based on metric learning (BDML). The main work of this paper is as follows: (1) the process of introducing metric learning in the social recommendation scenario is introduced in the form of equations, and explained the reason why metric learning can replace the click operation; (2) a new user bias is constructed to simultaneously model the impact of social relationships on user's ratings preferences and user's preferences; Experimental results on two datasets show that the BDML algorithm proposed in this study has better recommendation accuracy compared with other comparison algorithms, and will be able to guarantee the recommendation effect in a more sparse dataset.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.161-166
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• 2011

This study proposes a priority model for program directors in charge of Corporate Social Contribution to make the best decision. This empirical analysis aims to discover the most significant area among various programs of Corporate Social Contribution Activities. The Analytical Hierarchy Process (AHP) is used to test the priority model. The study attempts to demonstrate how the model helps providing better decision choices in corporate practices. The priority preference in Corporate Social Contribution Activities programs among corporate social contribution practitioners, PR professors and NGO activists are studied for their priority on corporate social contribution programs, among they valued com mon benefit social activity most important.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1065-1085
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• 2020

With rapid growth of content demands, device-to-device (D2D) content sharing is exploited to effectively improve the service quality of users. Considering the limited storage space and various content demands of users, caching schemes are significant. However, most of them ignore the influence of the asynchronous content reuse and the selfishness of users. In this work, the user preferences are defined by exploiting the user-oriented content popularity and the current caching situation, and further, we propose the social-aware rate, which comprehensively reflects the achievable contents download rate affected by the social ties, the caching indicators, and the user preferences. Guided by this, we model the collaborative caching problem by making a trade-off between the redundancy of caching contents and the cache hit ratio, with the goal of maximizing the sum of social-aware rate over the constraint of limited storage space. Due to its intractability, it is computationally reduced to the maximization of a monotone submodular function, subject to a matroid constraint. Subsequently, two social-aware collaborative caching algorithms are designed by leveraging the standard and continuous greedy algorithms respectively, which are proved to achieve different approximation ratios in unequal polynomial-time. We present the simulation results to illustrate the performance of our schemes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.121-128
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• 2017

This paper was to evaluate social enterprises' management efficiency with Data Envelope Analysis (DEA). The data was based on the 168 social enterprises' of annual performance reports published in 2015. The research focused on to measure both financial efficiency and social impact of the companies simultaneously. To apply DEA, the paper classified the enterprises into seven types based on types of socal impacts which each company provides before the estimation of the efficiency. The research results showed that group D, which employes disadvantaged people, provides social services and shares resources was the most efficient group and had higest net worths in Pure Technical Efficiency. In contrast, Group B, which only employs social advantage people and provides social service, was the least efficient one. The research suggests a practical and efficient framework in measuring social enterprises' management efficiency, including both the financial performance and social impacts simultaneously with their self-publishing reports. Because the Korea Social Enterprise Promotion Agency does not open business reports which social enterprises submit each year, there are basic limitations on researchers attempting to analyse with data from all social enterprises in Korea. Thus, this study dealt with only 10% of the social enterprises which self-published their performance report on the Korea Social Enterprise Promotion Agency's web site. Regardless of these limitations, this study suggested substantial methods to estimate management efficiency with the self-published reports. Because self-publishing is increasing each year, it will be the main source of information for researchers in examining and evaluating social enterprises' financial performance or social contribution. The research suggests a practical and efficient framework in measuring social enterprises' management efficiency, including both the financial performance and social impacts simultaneously with their self-publishing reports. The research results suggest not only list of efficient enterprises but also methods of improvement for less efficient enterprises.

• Journal of Engineering Education Research
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• v.24 no.6
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• pp.3-19
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• 2021

This study aimed to introduce a case study of a basic engineering design course using the ENACT model for fostering social responsibility of engineers, and to investigate the educational effects of the course. Since the ENACT model was designed to encourage STEM college students to pursue responsible problem solving based on their understanding of socioscientific issues, we assumed that it would be beneficial for engineering students to foster their social responsibility as well as their understanding of science/engineering-related issues. A total of 49 engineering students who enrolled in the course participated in the study. Data included students' course artifacts, reflection papers, and responses to survey questionnaires. Results indicated that the students became more aware of nature of science and technology after the program, and began to solve the problems while considering the views of multiple stakeholders. They highly valued the experience of communicating with others as engaging in the civic activities. They also expressed high satisfaction and feeling of achievement on the course learning. We expect the ENACT model to be an effective teaching guideline that fosters the social responsibility of engineering students and furthermore, engineering ethics.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1595-1606
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• 2018

Recently, there has been an increase in the number of social engineering techniques that indirectly attack the target system administrators or organizational weaknesses rather than the traditional technical cyber attacks that directly attacked the target systems. Accordingly, the type analysis and case study of social engineering techniques are being actively conducted. There has been, however, little effort to derive an analysis model that systematically analyzes social engineering based cyberspace operations. Therefore, this paper aims at building a Social Engineering Based Cyberspace Operations Analysis Model, which can be used as a reference framework for a case study or attack scenario generation of social engineering based cyberspace operations.