• 한국융합학회논문지
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• 제11권2호
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• pp.109-116
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• 2020

소셜 미디어는 예술가들의 작품 홍보 수단이자 판매 채널로서 급성장하고 있다. 하지만, 소셜 미디어는 근본적으로 거래를 위해 설계된 플랫폼이 아니기 때문에 거래를 진행함에 있어 신뢰와 안전성을 보장하기 어려운 다양한 한계를 가지고 있다. 본 논문에서는 예술가의 Profile, 작품과 관련된 정보, 거래에 대한 상세들을 블록체인 상에 기록하고 보존할 수 있도록 소셜 미디어와 블록체인 기반 스마트 계약 시스템을 연동하는 방안을 제안한다. 제안하는 연동을 통해 소셜 미디어 상에서 거래 참여자들은 상호 신뢰를 유지하며 투명하게 예술품 거래를 진행할 수 있다. 또한, 제안하는 연동은 기존 소셜 미디어를 수정할 필요 없이 소셜 미디어 개발사에서 제공하는 API나 Open source API로 구현 가능하게 구성된다. 본 연구는 소셜 미디어 상의 예술품 거래 방식을 보완하여 소셜 미디어 상의 예술품 거래 시장이 성장하는데 기여할 것으로 기대된다.

• 한국멀티미디어학회논문지
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• 제19권2호
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• pp.308-315
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• 2016

With the advancement in the area of cloud storage services as well as a tremendous growth of social networking sites, permission for one web service to act on the behalf of another has become increasingly vital as social Internet services such as blogs, photo sharing, and social networks. With this increased cross-site media sharing, there is a upscale of security implications and hence the need to formulate security protocols and considerations. Recently, OAuth, a new protocol for establishing identity management standards across services, is provided as an alternative way to share the user names and passwords, and expose personal information to attacks against on-line data and identities. Moreover, OwnCloud provides an enterprise file synchronizing and sharing that is hosted on user's data center, on user's servers, using user's storage. We propose a secure Social Networking Site (SSN) access based on OAuth implementation by combining two novel concepts of OAuth and OwnCloud. Security analysis and performance evaluation are given to validate the proposed scheme.

• Asia pacific journal of information systems
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• 제30권4호
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• pp.919-945
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• 2020

Social media platforms such as Instagram and Facebook lead to potential security risks, which consequently raise public concerns about privacy. However, most people rarely make active efforts to protect their personal data, even though they have shown increasing concerns about privacy. Therefore, this study examines the factors that determine social media users' behavior of using privacy settings and testifies the existence of privacy paradox in such a context. In addition, it investigates the mediating effects of implementation intentions on the relationship between intentions and behaviors. In the study, we collected data through questionnaires, and the respondents were undergraduate and graduate students in South Korea. After a pilot test (n = 92) and a set of face-to-face interviews, 266 usable responses were retrieved for data analysis finally. The results confirmed the existence of the privacy paradox regarding the use of social media privacy settings. And the implication intention did positively mediate the relationship between intention and behavior in the context of social media privacy settings. To the best of our knowledge, our study is the first in the information privacy literature to introduce the notion of implementation intention which is a much more powerful explanation and prediction of actual behavior than the (behavioral) intention.

• Journal of Information Technology Applications and Management
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• 제23권2호
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• pp.153-176
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• 2016

This study investigated factors affecting the use intention of podcast service users based on the unified theory of acceptance and use of technology (UTAUT). Performance expectancy, effort expectancy, social influence, facilitating condition, hedonic motivation, innovativeness, and media credibility were used as independent variables in the model. The survey data from the users of the podcast portal 'podbbang' were analyzed with Smart PLS 2.0 to test the structural equation model. The results revealed that the podcast service user's effort expectancy, facilitating condition, hedonic motivation, and media credibility have a significant influence on use intention. However, the relationship between the podcast service user's performance expectancy, social influence, innovativeness, and use intention were not identified as significant.

• The Journal of Asian Finance, Economics and Business
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• 제8권12호
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• pp.223-231
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• 2021

The study aimed to investigate the impact of social networks safety (SNS) on the marketing information quality (MIQ) during the COVID-19 pandemic in Saudi Arabia. The study examines the statistical differences in social networks safety SNS and marketing information quality MIQ according to the demographics such as age, sex, income, and education. For this study purpose, information security and privacy are two components of social networks safety. The research materials are website resources, regular books, journals, and articles. The population includes all Saudi users of social networks. The figures show that active users of the social network reached 25 Million in 2020. The snowball method was used and sample size is 500 respondents and the questionnaire is the tool for the data collection. The Structural Equation Modelling SEM technique is used. Convergent Validity, Discriminate Validity, and Multicollinearity are the main assumptions of structural equation modeling SEM. The findings show the high positive impact of SNS networks safety on MIQ and the statistical differences in such variables refer to education. Finally, the study presents a set of future suggestions to enhance the safety of social networks in Saudi Arabia.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.113-117
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• 2021

The article defines the basic concepts: "election campaign", "social capital", "conversion of social capital"; the principles and methods of research of social capital conversion in election campaigns are studied; the process of using social capital in politics is defined; ways of converting social capital into politics are considered; the possibilities of converting social capital in election campaigns are described. Election campaigns have been found to be a successful form of social capital conversion. The ability to use social capital in the election campaign speaks of its high potential. Election campaigns are not an effective use of social capital.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.238-246
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• 2021

The rapid rise of the Internet and social media has resulted in a large number of text-based reviews being placed on sites such as social media. In the age of social media, utilizing machine learning technologies to analyze the emotional context of comments aids in the understanding of QoS for any product or service. The classification and analysis of user reviews aids in the improvement of QoS. (Quality of Services). Machine Learning algorithms have evolved into a powerful tool for analyzing user sentiment. Unlike traditional categorization models, which are based on a set of rules. In sentiment categorization, Bidirectional Long Short-Term Memory (BiLSTM) has shown significant results, and Convolution Neural Network (CNN) has shown promising results. Using convolutions and pooling layers, CNN can successfully extract local information. BiLSTM uses dual LSTM orientations to increase the amount of background knowledge available to deep learning models. The suggested hybrid model combines the benefits of these two deep learning-based algorithms. The data source for analysis and classification was user reviews of Indian Railway Services on Twitter. The suggested hybrid model uses the Keras Embedding technique as an input source. The suggested model takes in data and generates lower-dimensional characteristics that result in a categorization result. The suggested hybrid model's performance was compared using Keras and Word2Vec, and the proposed model showed a significant improvement in response with an accuracy of 95.19 percent.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.305-316
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• 2021

The objective is to recognize the better opportunities from targeted reveal advertising, to show a banner ad to the consumer of online who is most expected to obtain a preferred action like signing up for a newsletter or buying a product. Discovering the most excellent commercial impression, it means the chance to exhibit an advertisement to a consumer needs the capability to calculate the probability that the consumer who perceives the advertisement on the users browser will acquire an accomplishment, that is the consumer will convert. On the other hand, conversion possibility assessment is a demanding process since there is tremendous data growth across different information dimensions and the adaptation event occurs infrequently. Retailers and manufacturers extensively employ the retail services from internet as part of a multichannel distribution and promotion strategy. The rate at which web site visitors transfer to consumers is low for online retail, out coming in high customer acquisition expenses. Approximately 96 percent of web site users concluded exclusive of no shopper purchase[1].This category of conversion rate is collected from the advertising of social media sites and pages that dataset must be estimating and assessing with the concept of big data clustering, which is used to group the particular age group of people along with their behavior. This makes to identify the proper consumer of the production which leads to improve the profitability of the concern.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.241-248
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• 2021

The article reviews the social media as an Internet phenomenon, determines their place and level of popularity in the society, as a result of which the social networks are a resource with perspective pedagogical potential. The analysis of social media from the point of view of studying a foreign language and the possibility of their usage as a learning medium has been carried out. The most widespread and popular platforms have been considered and, based on their capabilities in teaching all types of speech activities, the "Instagram", "Twitter", and "Facebook" Internet resources have been selected as the subject of the research. The system of tasks of teaching all types of speech activities and showing the advantages of the "Instagram", "Twitter", and "Facebook" platforms has been proposed and briefly reviewed.

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.305-311
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• 2022

This research aimed to provide a profound description of the practices of social media users in the Kingdom of Saudi Arabia (KSA), specifically the users of Facebook^® (FB) and Snapchat^® (SC), the reasons for these practices, decisions made, and the people involved. Such research would be of significant help to designers and policymakers of social media applications in understanding user practices when using social media applications and the reasons for such practices in the KSA. This better comprehension would be of significant help in improving current applications and creating new ones. According to the data analysis, there was a clear preference for SC over FB in the KSA. Most participants with SC accounts were described as very active users, accessing their accounts at least once a day compared to FB users. The users were led by this high preference for SC to create new words derived from the name of the application and use them in daily life. We showed our experience of carrying out a study in which the main objective was to collect factual empirical data from participants about their daily usage of social media applications while considering the unique cultural settings in the KSA. Mixed quantitative and qualitative methods were used to triangulate the data, increasing its trustworthiness and validity. Multiple perspectives were obtained using various data collection methods. Therefore, conclusions would not be confounded with limitations of any particular methodology or with conditions of any collection rounds. This research would constitute a valuable guide for researchers intending to use methods with male and female informants from different cultures, preparing them for potential challenges and suggesting possible solutions.