• Information Systems Review
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• v.18 no.3
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• pp.209-233
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• 2016

Internet companies that utilize social network have increased in number. The introduction of diverse social media services facilitated innovative changes in e-business. Social network service (SNS), which is a domain of social media, is a web-based service designed to strengthen human relations in the Internet and build new social relations. The remarkable growth of social network services and the profit generation and perception of this service are the new growth engines of this digital age. Given this development, many global IT companies views SNS as the most powerful form of social media. Thus, they invest efforts to develop business models using SNS.2) This study verifies the impact of privacy exposure in SNS as a result of privacy invasion. This study examines the purpose of using the SNS and user's awareness of the significance of personal information, which are key factors that affect self-disclosure of personal information. This study utilizes theory of reasoned action (TRA) to provide a theoretical platform that describes the specific behavior and emotional response of individuals. This study presents a research model that considers negative attitude (negatude). In this model, self-disclosure in SNS is considered a TRA. TRA is a subjective norm, a behavioral intention, and a key variable of exposure behavior. A survey was conducted on college students at Y university in Seoul to empirically verify the research model. The students have experiences in using SNS. A total of 198 samples were collected. Path analysis was applied to analyze the relations of factors. The results of path analysis show the statistically insignificant impact of privacy invasion on negatude, subjective norm, behavioral intention, and exposure behavior. The impact of unrecognized privacy invasion was also considered insignificant. The impacts of intention to use SNS on negatude, subjective norm, behavioral intention, and exposure behavior was significant. A significant impact was also found for the significance of personal information on subjective norm, behavioral intention, and exposure behavior, whereas the impact on negatude was insignificant. The impact of subjective norm on behavioral intention was significant. Lastly, the impact of behavioral intention on exposure behavior was insignificant. These findings are significant because the study examined the process of self-disclosure by integrating psychological and social factors based on theoretical discussion.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.21-34
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• 2011

Spam refers to any unwanted or unauthorized commercial messages. Spam may violate individuals' privacy or other personal rights. Spam often overloads network traffic, wastes individuals' time, lowers productivity and quality of life, and limits the trustworthiness of Internet businesses. As the use of mobile messaging services and social networking services both on mobile communication networks and on the Internet increase, newer and more complex types of IT applications and services are often used as new means of spam. In this research, the characteristics and impact of new and future forms of spam, and anti-spam related policies and regulations are surveyed. To improve the effectiveness of anti-spam policies and regulations in Korea, adding a definition of spam in the law, changing policies to focus on the 'type of services' rather on the medium of transmission, and redefining the scope of 'commercial purposes' in Korean law are suggested.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.903-921
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• 2024

Industry 5.0 puts forward higher requirements for smart cities, including low-carbon, sustainable, and people-oriented, which pose challenges to the design of smart cities. In response to the above challenges, this study introduces the cyber-physical-social system (CPSS) and parallel system theory into the design of smart cities, and constructs a smart city framework based on parallel system theory. On this basis, in order to enhance the security of smart cities, a sustainable patrol subsystem for smart cities has been established. The intelligent patrol system uses a drone platform, and the trajectory planning of the drone is a key problem that needs to be solved. Therefore, a mathematical model was established that considers various objectives, including minimizing carbon emissions, minimizing noise impact, and maximizing coverage area, while also taking into account the flight performance constraints of drones. In addition, an improved metaheuristic algorithm based on ant colony optimization (ACO) algorithm was designed for trajectory planning of patrol drones. Finally, a digital environmental map was established based on real urban scenes and simulation experiments were conducted. The results show that compared with the other three metaheuristic algorithms, the algorithm designed in this study has the best performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.51-73
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• 2023

Social media play a significant role in communicating information across the globe, connecting with loved ones, getting the news, communicating ideas, etc. However, a group of people uses social media to spread fake information, which has a bad impact on society. Therefore, minimizing fake news and its detection are the two primary challenges that need to be addressed. This paper presents a multi-modal deep learning technique to address the above challenges. The proposed modal can use and process visual and textual features. Therefore, it has the ability to detect fake information from visual and textual data. We used EfficientNetB0 and a sentence transformer, respectively, for detecting counterfeit images and for textural learning. Feature embedding is performed at individual channels, whilst fusion is done at the last classification layer. The late fusion is applied intentionally to mitigate the noisy data that are generated by multi-modalities. Extensive experiments are conducted, and performance is evaluated against state-of-the-art methods. Three real-world benchmark datasets, such as MediaEval (Twitter), Weibo, and Fakeddit, are used for experimentation. Result reveals that the proposed modal outperformed the state-of-the-art methods and achieved an accuracy of 86.48%, 82.50%, and 88.80%, respectively, for MediaEval (Twitter), Weibo, and Fakeddit datasets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.109-134
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• 2018

Collaborative Filtering (CF) is widely used in recommendation field, which can be divided into rating-based CF and learning-to-rank based CF. Although many methods have been proposed based on these two kinds of CF, there still be room for improvement. Firstly, the data sparsity problem still remains a big challenge for CF algorithms. Secondly, the malicious rating given by some illegal users may affect the recommendation accuracy. Existing CF algorithms seldom took both of the two observations into consideration. In this paper, we propose a recommendation method based on listwise learning-to-rank by incorporating users' social information. By taking both ratings and order of items into consideration, the Plackett-Luce model is presented to find more accurate similar users. In order to alleviate the data sparsity problem, the improved matrix factorization model by integrating the influence of similar users is proposed to predict the rating. On the basis of exploring the trust relationship between users according to their social information, a listwise learning-to-rank algorithm is proposed to learn an optimal ranking model, which can output the recommendation list more consistent with the user preference. Comprehensive experiments conducted on two public real-world datasets show that our approach not only achieves high recommendation accuracy in relatively short runtime, but also is able to reduce the impact of malicious ratings.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.123-148
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• 2015

Today the mobile devices including smart phones have influenced on the users' daily activities in the mobile internet society, and the expansion of social media has also affected on the purchasing behavior of consumers. This study examines whether the quality of corporate twitter, a typical social network service for call centers influences on the customer satisfaction, and brand loyalty. In order to achieve the research goal, the quality of twitter has been divided into four variables; information quality, service quality, system quality, and social quality. The results of our empirical analysis show that the three variables except service quality have significantly influenced on the customer satisfaction and the customer satisfaction also significantly has a casual effect on the brand loyalty. The empirical results are expected as a guideline to contribute on the practical improvement of customer service, satisfaction, and brand loyalty through corporate social network services such as corporate twitters in the future.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.690-698
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• 2013

Advanced digital environment, ease of life would bring significant benefits, but rather indiscriminate access to information have occurred new social problems. Especially the youth and children using the Internet to increase in population resulting from harmful information on the Internet, concerns about the negative impact increases establish policies for the protection of youth and children emphasizes the importance of various activities international community. Despite major countries aim to self-regulation minimize the direct regulation through collaboration with the private sector cultivation and campaign, continuing education, Korea was analyzed that implement direct and coercive enforcement regulations such as 'internet game shut down' and insufficient social infrastructure to create activities. Therefore, in order to create a positive internet environment, self-regulation is essential with private experts and organizations based on cooperation and indirect regulation.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.13-20
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• 2024

The purpose of this study is to objectively quantify the degree of social exclusion of the disabled and verify the impact of the derived degree of social exclusion on the quality of life of the disabled. And the purpose is to verify whether job satisfaction moderates the impact of social exclusion and quality of life of disabled people. The subjects of the study were 1,280 people extracted through a panel survey on employment of the disabled. The independent variables of social exclusion are economic difficulties, employment status, mental health, and social activities. The dependent variable was quality of life, and the control variable was job satisfaction. The research results are as follows. First, the sub-factors of social exclusion that affect quality of life were economic difficulties, mental health, participation in social activities, and employment status. Second, job satisfaction showed a moderating effect in the relationship between social exclusion and quality of life. And the sub-factors of social exclusion that have a moderating effect on quality of life were identified as economic difficulties, employment status, and social activities. In follow-up research, it will be necessary to investigate employment programs for the disabled in developed countries and analyze the implementation background, implementation details, achievements, and limitations, thereby contributing to the establishment of employment policies for the disabled. It is hoped that through this research, the vicious cycle of social exclusion and discrimination of the disabled will be improved and an opportunity will be provided to improve the quality of life through the economic activities of the disabled.

• The Journal of Information Systems
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• v.20 no.4
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• pp.205-232
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• 2011

With the rapid growth of internet technology, social commerce has played an important and central role in the online shopping area. Thus, we focus on the factors that influence on the adoption of social commerce. This study analyzes the relationship between perceived risk and the shopping motive in social commerce, and investigates whether the shopping motive significantly impact the purchase intention of the social commerce. The perceived risk is comprised of social risk and psychology risk, and the shopping motive is formed from personal motive and social motive. Finally, we analysis a moderating effect of collectivism. The results indicated that the personal motive was negatively affected by the social risk and psychology risk, and social motive was negatively affected by the psychology risk. The social risk and psychology risk had negative effect on the purchase intention, and personal motive and social motive had positive effect on the purchase intention of the social commerce. Finally, low collectivism seems to have the negative effect of the purchase intention by the perceived risk. The implications of integrating perceived risk and shopping motive into the proposed social commerce adoption model are discussed.

• Fashion & Textile Research Journal
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• v.15 no.5
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• pp.743-752
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• 2013

Consumers can share their diverse opinions about products due to the increased popularity of smartphones and the internet that enables increased access to the websites and encourages the use of 'SNS' (Social Network Services). Social commerce has expanded rapidly as a mainstream online shopping channel over the past year, compelling consumers to spend more money vis-$\grave{a}$-vis social commerce websites. This allows individuals to see different lists of prices for specific products; however, it is also likely to lead to serious compulsive buying. Despite these changing trends, earlier studies have been limited to factors that affect impulse purchases vis-$\grave{a}$-vis Internet shopping malls; therefore, in is salient to conduct research on consumer spending habits related to social commerce websites. This study describes the characteristics of consumers and utilizes social commerce websites as parameters for the impact of impulsive shopping based on a survey of 300 women in their 20's who have experienced impulse buying vis-$\grave{a}$-vis social commerce websites. This study shows that: First, discounts, product scarcity and social commerce site's reputation affect impulse buying when consumers buy products from the social commerce websites. Second, variables on the characteristics of the personal experiences, interests, and self-control also stimulate impulsive purchases.