• Analyses & Alternatives
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• v.2 no.2
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• pp.31-66
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• 2018

This study investigates the mobilizing function of political agreement and disagreement in communition mediated by social media. Analyses of a survey found that reception of news consistent with individual political predispositions through social networking sites (SNS) positively related to political participation, whereas reception of counterattitudinal news was unrelated. Similarly, SNS- based discussion with politically agreeing others predicted political participation, whereas discussion with disagreeing people did not contribute to participation. Moreover, attitude-consistent news reception and agreement in political discussion had interactive influences, as the effects of attitude-consistent news on participation become stronger with increases in discussion with agreement. The results suggest that the mobilizing effects of social media mainly work through political agreement rather than disagreement in communication.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.423-428
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• 2012

By shifting web2.0 users who share information from passive consumption and create their own information and exchange in the form of an active and visible appearance was changing. Most simply and easily with features that can be accessed. SNS is native to Korea me2day, Cyworld, (c) Logs and foreign SNS of Facebook, Twitter and a surge in user FramVille, Mafia War's Game, and many users use to SNG are. SNG's compared to the foreign national is active and not yet is a step. The domestic market, the benefits of this game online games and SNS in vogue these days to incorporate the concept in the market for a new form of the domestic game that the game, SNOG (Social Network Online Game, social networks, online games) to the expansion of flexible development direction, Expand accessibility, expansion of social skills is to present to the three.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.9
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• pp.331-336
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• 2015

On the IoT-based sensor networks, users or sensor nodes must perform a Service Discovery (SD) procedure before access to the wanted service. Current approach uses a center-concentrated Resource Directory (RD) servers or P2P technique, but these can cause a point-of-failure or flooding of SD messages. In this paper, we proposes an improved SWoT SD approach for CoAP-based sensor networks, which integrates Social Web of Things (SWoT) concept to current CoAP-based SD approach that makes up for weak points of existing systems. This new approach can perform a function like a keyword or location-based search originated from SNS, which can enhances the usability. Finally, we implemented a real system to evaluate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.454-462
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• 2018

This study was conducted to examine SNS addiction proneness and interpersonal satisfaction among undergraduate students and the relationships between these two variables, as well as to establish baseline data for appropriate intervention of SNS addiction prevention. The participants of this study were 316 undergraduate students in D and K city, and data were collected between June 30 and July 30, 2017. Data were collected by a self-administered online survey and analyzed by descriptive statistics, t-tests, and Pearson's correlation coefficients using SPSS. The results showed that SNS addiction proneness and interpersonal satisfaction were negatively correlated (r=-0.57, p<0.01), indicating students with higher SNS addiction had lower interpersonal satisfaction. There were no significant differences in SNS addiction proneness and interpersonal satisfaction by gender (t=0.05, p=0.963), number of SNS networks (t=0.66, p=0.513), or number of SNS-only networks (t=-1.24, p=0.216). Students who used SNS for data collection showed significantly higher interpersonal satisfaction (t=3.02, p=0.030); however, there was no significant differences in SNS addiction proneness among purposes for using SNS (t=0.39, p=.759). The results of this study will be useful baseline data for developing an intervention to improve interpersonal satisfaction and prevent SNS addiction among undergraduate students.

• Journal of Information Science Theory and Practice
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• v.9 no.1
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• pp.24-34
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• 2021

The popularity of social networking sites (SNS) has facilitated communication between users. The usage of SNS helps users in their daily life in various ways such as sharing of opinions, keeping in touch with old friends, making new friends, and getting information. However, some users misuse SNS to belittle or hurt others using profanities, which is typical in cyberbullying incidents. Thus, in this study, we aim to identify profane words from the ASKfm corpus to analyze the profane word distribution across four different roles involved in cyberbullying based on lexicon dictionary. These four roles are: harasser, victim, bystander that assists the bully, and bystander that defends the victim. Evaluation in this study focused on occurrences of the profane word for each role from the corpus. The top 10 common words used in the corpus are also identified and represented in a graph. Results from the analysis show that these four roles used profane words in their conversation with different weightage and distribution, even though the profane words used are mostly similar. The harasser is the first ranked that used profane words in the conversation compared to other roles. The results can be further explored and considered as a potential feature in a cyberbullying detection model using a machine learning approach. Results in this work will contribute to formulate the suitable representation. It is also useful in modeling a cyberbullying detection model based on the identification of profane word distribution across different cyberbullying roles in social networks for future works.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1168-1173
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• 2013

This paper proposes a new visualization method based on cloud technique which uses internal relationship of user correlation and external relation of social network to visualize user relationship hierarchy. The visualization method of this paper can well represent user-focused relationship hierarchy on social networks by a correlation matrix. The importance of a access node reflects into user relationship hierarchy by exploiting external relation of social network. Users of the method can well understand user relationships on account of representing user relationship hierarchy from social networks. In addition, the method use hadoop and hive for distribution storing and parallel processing which the result of calculation visualizes hierarchy graph using D3.

• Journal of Service Research and Studies
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• v.4 no.1
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• pp.21-35
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• 2014

Many people have a social network service (SNS) by utilizing a variety of community activities, information sharing, and the creation of social networking. In terms of marketing academics view social networks between businesses and consumers in the new communication strategy, a new way to make them in terms of marketing a new business opportunity. That is, they are actively engaged in the various marketing activities targeting customers using SNS. According to H. A. Simon's needle theory, it is efficient to make a decision within the bounded rationality due to the difficulty of collecting data in decision-making as well as the inability to collect all information because of limited time and money. If the information or the informant can be trusted, the customers would be able to make a quick decision and get higher satisfaction from it. Therefore, this study examines and thereby empirically demonstrates what role customers' trust plays in a company's marketing using SNS by exploring how trust condition works in the mediated model and, theoretically, intends to introduce an empirical methodology on more strictly mediated moderating effects and, in practice, revisit the role of trust on direct and indirect effect the SNS's Information quality has on the performance variables such as customer satisfaction and loyalty. This study thereby aims to provide a strategic tool for the companies that plan to use the SNS in developing marketing strategies.

• Smart Media Journal
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• v.11 no.1
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• pp.58-66
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• 2022

As Internet technology develops, SNS users are increasing. As SNS becomes popular, SNS-type crimes using the influence and anonymity of social networks are increasing day by day. In this paper, we propose a fake account classification method that applies machine learning and deep learning to statistical and image data for fake accounts classification. SNS account data used for training was collected by itself, and the collected data is based on statistical data and image data. In the case of statistical data, machine learning and multi-layer perceptron were employed to train. Furthermore in the case of image data, a convolutional neural network (CNN) was utilized. Accordingly, it was confirmed that the overall performance of account classification was significantly meaningful.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1975-1976
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• 2011

소셜네트워크의 등장은 기업 환경에도 많은 변화를 가져오고 있다. 초기의 기업 소셜네트워크서비스(SNS)는 자사 고객들과의 커뮤니케이션 채널로 활용되었지만, 최근의 기업 SNS는 자사내의 조직강화 수단으로 인식되기 시작하고 있다. 직원들의 수평적인 아이디어 뱅크와 인맥 형성(Human networks)을 위해서 많은 기업들이 SNS 활용을 시도하고 있다. 기업 SNS의 활용도가 높아지기 위해서는 Anywhere, Anytime 접근 환경이 지원되어야 한다. 기존 SNS 활용도를 폭발적으로 증가시킨 스마트폰과 같은 모바일 단말 지원도 기업 SNS에서도 이루어져야 한다. 그러나, 모바일 단말은 PC와 같은 기존 사용자 환경에 비해서 보안적으로 많은 취약점을 갖고 있다. 이 논문에서는 기업 SNS에모바일 단말 활용 시 대두될 수 있는 보안 취약성을 점검하고, 그에 대한 대응책을 제시한다.

• Journal of the Korea society of information convergence
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• v.7 no.2
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• pp.49-57
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• 2014

Recently, opinion mining is introduced to extract useful information from SNS data and to evaluate the true intention of users. Opinion mining are required several efficient techniques to collect and analyze a large amount of SNS data and extract meaningful data from them. Therefore in this paper, we propose a parallel HDFS(Hadoop Distributed File System) and emotion functions based on Mapreduce to extract some emotional information of users from various unstructured big data on social networks. The experiment results have verified that the proposed system and functions perform faster than O(n) for data gathering time and loading time, and maintain stable load balancing for memory and CPU resources.