• Journal of KIISE:Information Networking
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• v.37 no.2
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• pp.94-98
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• 2010

In this paper, we formalize a new adaptive online price control scheme based on the Stackelberg game model. By using the hierarchical interaction strategy, control decisions in each mechanism act cooperatively and collaborate with each other to satisfy conflicting performance criteria. In addition, our dynamic online approach is practical for real network implementation. With a simulation study, the proposed scheme can adaptively adjust the network price to approximate an optimized solution under widely diverse network situations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.243-258
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• 2017

Recently, Due to advances in smart-phones and mobile devices, the use of SNS is increasing in recent years. Online networking is building new paradigms in terms of creating personal needs. Along with the nature of mobile devices, it is expected to have a lot of impact on SNS service participation. The study focused on the effect of SNS on SNS participation and ease of use of social characteristics and ease of use of SNS. A survey was conducted on a survey of SNS users and analyzed the data through the structural equations. The study found that the study of social networking was statistically significant in terms of the intent of identifying the usefulness of SNS and ease of use and ease of use.

• The Research Journal of the Costume Culture
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• v.25 no.1
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• pp.88-103
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• 2017

The rapid growth in the popularity of social media sites has meant that social media has become an important communication channel for brands. Brands create brand pages on social media to cultivate positive and strong relationships with consumers. This study seeks to enhance our understanding of how fashion brand pages in social media foster consumer-brand relationships by exploring the factors that affect the development of consumer-brand relationships. Drawing on the parasocial interaction theory, this study proposes parasocial interaction as a key factor of this process. Specifically, this study proposes four antecedents (vividness, interactivity, social presence, and focused attention) of consumers' parasocial interaction with brand pages, which further affects consumer responses in terms of affective engagement and brand loyalty. An online survey was administered with consumers who have followed and visited at least one fashion brand page via a social networking site (SNS). Structural equation modeling revealed that consumers' perceptions of vividness, interactivity, social presence, and focused attention on a fashion brand page positively affected their feelings towards parasocial interaction with the brand page, which in turn led to their affective engagement with the brand page and consequent brand loyalty. These findings suggest that consumers build relationships of varying degrees with brand pages in a similar manner to that with people, which leads to their development of a positive relationship with the brand. This study concludes with discussions and practical implications.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.59-66
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• 2023

Text mining (TM) is most widely used to find patterns from various text documents. Cyber-bullying is the term that is used to abuse a person online or offline platform. Nowadays cyber-bullying becomes more dangerous to people who are using social networking sites (SNS). Cyber-bullying is of many types such as text messaging, morphed images, morphed videos, etc. It is a very difficult task to prevent this type of abuse of the person in online SNS. Finding accurate text mining patterns gives better results in detecting cyber-bullying on any platform. Cyber-bullying is developed with the online SNS to send defamatory statements or orally bully other persons or by using the online platform to abuse in front of SNS users. Deep Learning (DL) is one of the significant domains which are used to extract and learn the quality features dynamically from the low-level text inclusions. In this scenario, Convolutional neural networks (CNN) are used for training the text data, images, and videos. CNN is a very powerful approach to training on these types of data and achieved better text classification. In this paper, an Ensemble model is introduced with the integration of Term Frequency (TF)-Inverse document frequency (IDF) and Deep Neural Network (DNN) with advanced feature-extracting techniques to classify the bullying text, images, and videos. The proposed approach also focused on reducing the training time and memory usage which helps the classification improvement.

• Journal of the Society of Disaster Information
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• v.8 no.1
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• pp.1-9
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• 2012

Informatization of society through the computer and the Internet, because large amounts of information production and exchange and new way of communicating is born. Passive way past the one-sided information flows actively interact to evolve in a manner of information producers and information consumers distinction and personal relationships that enhance the online Social Networking Service (SNS) has developed into the social structure of. Thus, the spread of information work closely with the social network structure spark social conflict may act as a factor, and systems and the environment, personal and cultural adaptation of speed to keep up with the rapid development of science and technology as the inability conflict and confusion should lead to even. This paper the characteristics of the information society, with a look at the evolution of social risk factors as the wavelength of information about this look at the role of private security sought to evaluate. Information Society in time and space by shrinking the area of human life that has brought the convenience and simplicity, whereas the non-performance due to the nature of anonymous raises many social side-effects are. This made the preparation of national regulatory measures, but for the protection of personal protection devices in the private sector has not yet been discussed. Way of life and property of the purchaser to protect an individual's private security will have to charge it.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.173-180
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• 2016

SOA has been adopted by enormous number of organizations world-wide. This study has investigated significant factors which affect SOA adoption in positive and negative manner. Unlike the previous similar studies, where they focused on qualitative analysis for SOA adoption, this study conducted a quantitative analysis to investigate the relationship between the adoption of SOA and the performance of IT organizations. In order to conduct the research, an online questionnaire was created and distributed among SOA experts through the social networking platform of professionals, LinkedIn. Total one hundred and four (104) respondents from thirty (30) different countries participated in this study. The results of this study indicate that there are both positive and negative influences upon SOA adoption. The positive influences includes: governance, strategy, culture and communication, business and IT alignment and ROI; whereas complexity, security concerns, and costs have negatively affected SOA adoption.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.7-13
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• 2024

User preferences and ratings may be anticipated by recommendation systems, which are widely used in social networking, online shopping, healthcare, and even energy efficiency. Constructing trustworthy recommender systems for various applications, requires the analysis and mining of vast quantities of user data, including demographics. This study focuses on holding elections with vague voter and candidate preferences. Collaborative user ratings are used by filtering algorithms to provide suggestions. To avoid information overload, consumers are directed towards items that they are more likely to prefer based on the profile data used by recommender systems. Better interactions between governments, residents, and businesses may result from studies on recommender systems that facilitate the use of e-government services. To broaden people's access to the democratic process, the concept of "e-democracy" applies new media technologies. This study provides a framework for an electronic voting advisory system that uses machine learning.

• Information Systems Review
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• v.13 no.1
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• pp.33-59
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• 2011

Although online social network services widely used in human networking and recruiting industries, it is showing off its limitations in followings-it's hard to reach the status of seamless connection between offline and online; the incompletion and low credibility of the information came from non-face-to-face profile exchange; and the restraint of user autonomy due to centralized control. This paper defines the ubiquitous social network management which enables the seamless real-time face-to-face social interactions of the users based on WPAN (Wireless Personal Area Network) who share the same interest in real word and deduces a ubiquitous social network management framework based on it. As an instance of ubiquitous social network management, u-Recruiting service model will be designed and analyzed. The Analysis using the business model will be followed by the possible scenario of service model. The role, value proposition and potential benefits of the each participants in this service model and will be given as well. In order to evaluate relative advantages of the model suggested by this study, 6 cases will be compared.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.145-158
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• 2022

Although the rapid development of technology has led to a swift increase in the number of companies using social networking services (SNS), it will not be accurate to say that they have fully "utilized" the functionality of SNS simply by "using" these services. Therefore, this study aims to increase the convenience of using digital technology and help SNS users in extending the functionality of these services beyond their regular use and thus, revitalize the field by increasing the service providers' efficiency. In this study, the Facebook usage status of a graduate school newspaper from an undisclosed university in Seoul was analyzed from February to December, 2021 using the participant observation method. The results of the study revealed the following: First, it is necessary to diversify the subject and type of content to ensure a continuous supply of quality content; Second, there is a need to examine the user categories and characteristics by utilizing SNS functionalities such as, the target reports and insights, and based on this, supply content that meets the needs of the users; Third, to resolve the problem of low levels of user participation and an inactive Facebook account, it is necessary to mobilize new marketing tools like online events. The significance of this study is that it confronts the real problems faced by some companies that cannot keep pace with market changes in a digital environment, identifies failure factors, and proposes solutions to them.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.112-119
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• 2023

Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.