• The Journal of Information Systems
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• v.23 no.1
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• pp.93-109
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• 2014

This study aims to develop a rich understanding of user goals in user-empowering information technologies which have been dominating part in the information systems environment. A particular focus is on users' goals in a social network site (SNS) which is a typical example of user-empowering technologies. Users conduct various activities in order to achieve diverse goals in SNS. Thus, investigating what goals users pursue in SNS will give insights into understanding the users. We employed the laddering interview technique and means-end chain approach. Interviews of 50 Facebook users were analyzed to produce a hierarchical goal map showing users' goal structure. The map contains 18 goals, including self-reflection, psychological stability, belongingness, improving productivity, and amusement as ultimate goals in SNS. In the map, there are varied routes from activities to ultimate goals in SNS; that is, a complex assembly consisting of activities and goals. The findings call the information systems research community to have more interests in diverse goals and values users seek with technologies.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.05a
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• pp.199-201
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• 2013

In a construction project in which cooperation among project members gets its importance, trust among construction site members should be foundation to enhance team spirit and achievement. This study analyzes the trust network among staff by using social network analysis (SNA) theory for organizations in apartment complex construction sites in Korea. The analysis illustrates higher level of trust for those positioning in the higher positions in hierarchy and having greater experiences. It might be attributable to own features of construction works where skills are acquired by site experience.

• Journal of Information Management
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• v.40 no.2
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• pp.1-24
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• 2009

This study explored the scientific web spaces of Korea and Japan by applying webmetric and social network analysis techniques with the aim of ascertaining international scholarly communication characteristics between the two countries. In general, more links were generated from the Korean scientific web sites to the Japanese sites than those from the opposite direction, thus implying a higher usage of Japanese scientific information on the web in Korean sites. In addition, university sites in the two countries were highly linked on the web revealing the most active institutions in scholarly communication were the universities. Based on the link analysis, the study also indicated which country was more dependent on the other in scholarly communication in specific scientific fields.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.1-6
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• 2023

Text mining (TM) is most widely used to process the various unstructured text documents and process the data present in the various domains. The other name for text mining is text classification. This domain is most popular in many domains such as movie reviews, product reviews on various E-commerce websites, sentiment analysis, topic modeling and cyber bullying on social media messages. Cyber-bullying is the type of abusing someone with the insulting language. Personal abusing, sexual harassment, other types of abusing come under cyber-bullying. Several existing systems are developed to detect the bullying words based on their situation in the social networking sites (SNS). SNS becomes platform for bully someone. In this paper, An Enhanced text mining approach is developed by using Ensemble Algorithm (ETMA) to solve several problems in traditional algorithms and improve the accuracy, processing time and quality of the result. ETMA is the algorithm used to analyze the bullying text within the social networking sites (SNS) such as facebook, twitter etc. The ETMA is applied on synthetic dataset collected from various data a source which consists of 5k messages belongs to bullying and non-bullying. The performance is analyzed by showing Precision, Recall, F1-Score and Accuracy.

• The Journal of Information Systems
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• v.18 no.4
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• pp.87-103
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• 2009

Although the Internet has been a important communication tool in modem societies, researchers did not pay attention to its' positive impacts on individual's psychological process. The Internet provides users with a unique environment such as visual isolation, non face-to-face communication, and easiness to escape from social influences. This environment enables people to take free action according to their personality and disclose themselves. From the uses and gratification perspective, the current research reveals that individuals with high extraversion are inclined to maintain social networking sites and those with high openness participate in web communities. The findings indicate that individuals' social use of the internet may reflect their personality. This study, also, reveals that controlling the big five personality dimensions, the amount of self-disclosure through ones' social networking site is positively related with subjective happiness. This finding suggests that like confession behaviors in religious or curing facilities, people can use the Internet as a therapeutic or a preventative method for promoting their well-being. Theoretical contributions and practical implications are discussed.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.196-198
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• 2016

Online social networking sites such as MySpace, Facebook, Twitter are becoming very preeminent, and the quantities of their users are escalating very quickly. Due to the significant escalation of security vulnerabilities in social networks, user's confidentiality, authenticity, and privacy have been affected too. In this paper, a short study of online social network attacks is presented in order to identify the problems and impact of the attacks on World Wide Web (WWW).

• 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.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.131-142
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• 2021

Recently, there has been an active service that provides customized news to news subscribers. In this study, we intend to design a customized news service system through Deep Learning-based Social Network Service (SNS) activity analysis, applying real news and avoiding fake news. In other words, the core of this study is the study of delivery methods and delivery devices to provide customized news services based on analysis of users, SNS activities. First of all, this research method consists of a total of five steps. In the first stage, social network service site access records are received from user terminals, and in the second stage, SNS sites are searched based on SNS site access records received to obtain user profile information and user SNS activity information. In step 3, the user's propensity is analyzed based on user profile information and SNS activity information, and in step 4, user-tailored news is selected through news search based on user propensity analysis results. Finally, in step 5, custom news is sent to the user terminal. This study will be of great help to news service providers to increase the number of news subscribers.

• Journal of Information Technology Applications and Management
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• v.20 no.4
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• pp.191-205
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• 2013

Recently, the topic of predicting interpersonal trust in online social networks is receiving considerable attention, because trust plays a critical role in controlling the spread of distorted information and vicious rumors, as well as reducing uncertainties and risk from unreliable users in social networks. Several trust prediction models have been developed on the basis of transitivity and composability properties of trust; however, it is hard to find empirical studies on whether and how transitivity and composability properties of trust are operated in real online social networks. This study aims to predict interpersonal trust between two unknown users in social networks and verify the proposition on whether and how transitivity and composability of trust are operated in social networks. For this purpose, we chose three social network sites called FilmTrust, Advogato, and Epinion, which contain explicit trust information by their users, and we empirically investigated the proposition. Experimental results showed that trust can be propagated farther and farther along the trust link; however, when path distance becomes distant, the accuracy of trust prediction lowers because noise is activated in the process of trust propagation. Also, the composability property of trust is operated as we expected in real social networks. However, contrary to our expectations, when the path is synthesized more during the trust prediction, the reliability of predicted trust did not tend to increase gradually.

• Journal of Service Research and Studies
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• v.5 no.1
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• pp.79-89
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• 2015

Recently, with the introduction of social network services, studies that try to make use of them for the various purposes have been actively investigated. In order to proceed with the research that takes advantage of social network services, it is necessary to review the relevant literature and to identify trends in researches. However, the researches of social network are massive amount, so to review the huge amount of relevant research literature is a very difficult task. Therefore, in this study, we analyze systematically the tendency of research related to social network service focusing on Twitter. Especially, we use the SLR (Systematic Literature Review) technique for systematic literature survey and analysis. For the literature survey, we select korean literature resource sites and 243 studies of literature that are surveyed. Studies and analyzes on Twitter in a variety of research studies were also using Twitter data that way beyond the simple question directly.