• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.202-206
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• 2023

Today, social media has become a vital tool. The world communicates and reaches the news and each other's opinions through social media accounts. Recently, considerable research has been done on analyzing social media due to its rich data content. At the same time, since the beginning of the COVID-19 pandemic, which has afflicted so many around the world, the search for a vaccine has been intense. There have been many studies analyzing people's feelings during a crisis. This study aims to understand people's opinions about available Coronavirus vaccines through a learning model that was developed for this purpose. The dataset was collected using Twitter's streaming Application Programming Interface (API) , then combined with another dataset that had already been collected. The final dataset was cleaned, then analyzed using Python. Polarity and subjectivity functions were used to obtain the results. The results showed that most people had positive opinions toward vaccines in general and toward the Pfizer one. Our study should help governments and decision-makers dispel people's fears and discover new symptoms linked to those listed by the World Health Organization.

• Knowledge Management Research
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• v.15 no.2
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• pp.165-182
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• 2014

Social commerce is regarded as a kind of e-commerce that utilizes social media. Considering increasing complaints around social commerce market, it is important to see customers' satisfaction level and intentions to repurchase. In this study, we examine antecedents that affect customers' satisfaction and relationship between satisfaction and intention to repurchase in social commerce market. We also use social media characteristics as moderators between antecedents and customers' satisfaction. The main results are as follows. First, except site design, most of the intrinsic factors of service quality, such as information, transaction, communication and perceived security had positive effects on customers' satisfaction. Second, all the extrinsic factors of service quality, such as discount rate, constraints, and discrimination had significant impacts on customers' satisfaction. Third, the social media characteristics could not moderate the relationship between service qualities and customers' satisfaction. Fourth, customers' satisfaction had positive effect on the intention to spread through social media. Fifth, customers' satisfaction had positive effect on the intention to repurchase. Social commerce companies need to set up strategies considering the antecedents of customers' satisfaction using these research results. They also need to secure customers that have sustainable purchasing intentions.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.127-133
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• 2021

Today, phishing attacks represent one of the biggest security threats targeting users of the digital world. They consist of an attempt to steal sensitive information, such as a user's identity or credit and debit card details, using various methods that include fake emails, fake websites, and fake social media messages. Protecting the user's security and privacy therefore becomes complex, especially when those users are children. Currently, children are participating in Internet activity more frequently than ever before. This activity includes, for example, online gaming, communication, and schoolwork. However, children tend to have a less well-developed knowledge of privacy and security concepts, compared to adults. Consequently, they often become victims of cybercrime. In this paper, the effects of security awareness on users who are children are investigated, looking at their ability to detect phishing attacks in social media. In this approach, two Experiments were conducted to evaluate the effects of security awareness on WhatsApp application users in their daily communication. The results of the Experiments revealed that phishing awareness training has a significant positive effect on the ability of children using WhatsApp to identify phishing messages and thereby avoid attacks.

• Journal of the Korea Convergence Society
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• v.11 no.2
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• pp.109-116
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• 2020

Social media is growing rapidly as a means of promoting artists' artworks and a channel for sales. However, since social media is not fundamentally a platform designed for trading, it has various limitations that make it difficult to ensure trust and security in carrying out transactions. In this paper, it is proposed interoperability between social media and blockchain-based smart contract system that can record and preserve the artist's profile, information related to artworks and details of the contract on the blockchain. The proposed interoperability allows artwork trading participants on social media to maintain mutual trust and to conduct the contract transparently. Also, the proposed interoperability consists of an API provided by the social media developer or an open source API without having to modify existing social media. This study is expected to contribute to the growth of the art trading market on social media by complementing the art trading practices on social media.

• Journal of Korea Multimedia Society
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• v.19 no.2
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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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• v.30 no.4
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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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• v.23 no.2
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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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• v.8 no.12
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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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• v.21 no.9
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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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• v.21 no.8
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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.