• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.131-136
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• 2021

This research aims to analyse the practices adopted by social media users in the Kingdom of Saudi Arabia (KSA), specifically users of Facebook and Snapchat. To collect data from participants, a questionnaire was used, generating 915 responses. The analysis of the data shows a clear preference for Snapchat over Facebook in the KSA, where 89% of the participants have accounts on Snapchat compared to 66% of them with accounts on Facebook. Moreover, the preference for Snapchat over Facebook has been clearly shown in the daily usage of participants, where 83% of those with Snapchat accounts can be described as very active users. They have accessed their Snapchat accounts at least once a day compared to only 15% of Facebook users. Different reasons were provided by the participants explaining the practices they adopted. We believe that such research could help social media applications' designers and policy makers to understand the behaviour of users in the KSA when using social media applications and the rationale behind their behaviour and preferences. This understanding could help improve the performance of current applications and new ones.

• Journal of Korea Multimedia Society
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• v.20 no.7
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• pp.1136-1147
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• 2017

In this study, we investigated the effect of users' emoticon usage on their satisfaction with image making and self-expression in MIM communication. We defined internal attraction, social appeal, and communication ability as personal image making factors due to the use of emoticons in MIM communication. And we defined the research hypotheses based on the definition of intimacy, openness, and social reality as relational image making factors. In MIM communication, we analyzed the questionnaire about emoticon users. As a result, emoticon usage was found to have a positive and significant effect on self-expression in relation image making rather than personal image making. The study implies that the use of emoticons can lead to image making in MIM communication and satisfy the satisfaction of self expression.

• Journal of Information Technology Applications and Management
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• v.28 no.1
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• pp.95-110
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• 2021

This study aims to explore the Internet personal broadcasting quality factors that influence viewer satisfaction and dissatisfaction based on the motivation-hygiene theory. Specifically, the quality factors that affect viewer satisfaction of Internet personal broadcasting are derived from the perspectives of extrinsic (contents usefulness and media usability), intrinsic (emotional/cognitive/behavioral enjoyment and creator characteristics), and social motivation (visibility, subjective norm, image, sociality). The data of 200 respondents was used to analyze the relative impact of satisfaction and dissatisfaction with the Kano model, which assumes that viewer satisfaction at both functional and emotional levels varies over quality attributes. In the empirical analysis, the quality factors were classified into attractive, one-dimensional, must-be, and indifferent quality. In addition, it was found that the customer satisfaction coefficient was high in the order of uniqueness, differentiation, and visibility. On the other hand, as a result of applying the dissatisfaction coefficient, it was identified in the order of donation, content reliability, and creator responsiveness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.540-546
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• 2014

Recently a new government has announced an action plan known as the government 3.0, which aims to provide customized services for individual people, generate more jobs and support creative economy. Leading on from previous similar initiatives, the new scheme seeks to focus on open, share, communicate, and collaborate. In promoting Government 3.0, the crucial factor might be how to align the core services and policies of Government 3.0 with correspoding technologies. The paper describes the concepts and features of Government 3.0, identifies emerging Internet-based technologies and services toward the initiative, and finally provides improvement plans for Government 3.0. As a result, 10 issues to be brought together include: Smart Phone Applications and Service, Mobile Internet Computing and Application, Wireless and Sensor Network, Security & Privacy in Internet, Energy-efficient Computing & Smart Grid, Multimedia & Image Processing, Data Mining and Big Data, Software Engineering, Internet Business related Policy, and Management of Internet Application.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.719-728
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• 2016

In this paper, we analyzed IoT patent data using the social network analysis of keyword community network in patents related to Internet of Things technology. To identify the difference of IoT patent trends between Korea and USA, 100 Korea patents and 100 USA patents were collected, respectively. First, we first extracted important keywords from IoT patent abstracts using the TF-IDF weight and their correlation and then constructed the keyword network based on the selected keywords. Second, we constructed a keyword community network based on the keyword community and performed social network analysis. Our experimental results showed while Korea patents focus on the core technologies of IoT (such as security, semiconductors and image process areas), USA patents focus on the applications of IoT (such as the smart home, interactive media and telecommunications).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.43-49
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• 2019

The wired and wireless Internet is a useful window to easily acquire various types of media data. On the other hand, the public can easily get the media data including the object to which the personal information is exposed, which is a social problem. In this paper, we propose a method to robustly detect a target object that has exposed personal information using a learning algorithm and effectively block the detected target object area. In the proposed method, only the target object containing the personal information is detected using a neural network-based learning algorithm. Then, a grid-like mosaic is created and overlapped on the target object area detected in the previous step, thereby effectively blocking the object area containing the personal information. Experimental results show that the proposed algorithm robustly detects the object area in which personal information is exposed and effectively blocks the detected area through mosaic processing. The object blocking method presented in this paper is expected to be useful in many applications related to computer vision.