• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.9-16
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• 2023

The natural language on social network platforms has a certain front-to-back dependency in structure, and the direct conversion of Chinese text into a vector makes the dimensionality very high, thereby resulting in the low accuracy of existing text classification methods. To this end, this study establishes a deep learning model that combines a big data ultra-deep convolutional neural network (UDCNN) and long short-term memory network (LSTM). The deep structure of UDCNN is used to extract the features of text vector classification. The LSTM stores historical information to extract the context dependency of long texts, and word embedding is introduced to convert the text into low-dimensional vectors. Experiments are conducted on the social network platforms Sogou corpus and the University HowNet Chinese corpus. The research results show that compared with CNN + rand, LSTM, and other models, the neural network deep learning hybrid model can effectively improve the accuracy of text classification.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.7
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• pp.837-844
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• 2015

A research of Social Network is focused to the single node and link. But when we consider the complexity of Social Network, I think we need the analysis of integrated influence by multiple nodes that satisfied with specific condition. But, the study of this area don't process apart from Sub-network concept. The purpose of this paper is to focus on the analysis of influence by multiple nodes. For it, I define a new term as Group Node, and it express multiple nodes that satisfied a specific condition. And I propose a method for reconstruction by using Group Node in Social Network. and I make a program that produce a Group Node satisfied with a special condition by using Genetic Algorithm, and show the result. I hope this result can be a start point of the Social Network analysis based on Group Node.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.113-119
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• 2020

Numerous tourist-related data produced on the Internet contain not only simple tourist information but also diverse ideas and opinions from users. In order to derive meaningful information about tourist sites from such big data, the social network analysis of tourist keywords can identify the frequency of keywords and the relationship between keywords. Thus, it is possible to make recommendations more suitable for users by utilizing the clear recommendation criteria of tourist attractions and the relationship between tourist attractions. In this paper, a recommendation system was designed based on tourist site information through big data social network analysis. Based on user personality information, the types of tourism suitable for users are classified through deep learning and the network analysis among tourist keywords is conducted to identify the relationship between tourist attractions belonging to the type of tourism. Tour information for related tourist attractions shown on SNS and blogs will be recommended through tagging.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2586-2592
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• 2010

Currently social network games with an emphasis on the relationship between the friends, especially women users and the elderly users of over forties, have contributed to the expansion of game market attracting large audiences. Though recent interest in social network games and the explosive propagation of social network game into game industry, scholarly research for social network game is insufficient. The objective of the study is to explore the success factors for successful social network games through the depth interview with game experts. We suggest the guidelines for development of social network game. Commercial success of social network games and the number of users with the best game, farmville, were investigated for understanding key success factors in social network game field. As a result, social interaction, simple interface, asynchronous method, instrumental rationality factors have been identified. This result of the study will expect the guideline in order to develop a successful social network games.

• ETRI Journal
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• v.34 no.4
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• pp.591-601
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• 2012

Unstructured peer-to-peer (p2p) networks usually employ flooding search algorithms to locate resources. However, these algorithms often require a large storage overhead or generate massive network traffic. To address this issue, previous researchers explored the possibility of building efficient p2p networks by clustering peers into communities based on their social relationships, creating social-like p2p networks. This study proposes a social relationship p2p network that uses a measure based on Hebbian theory to create a social relation weight. The contribution of the study is twofold. First, using the social relation weight, the query peer stores and searches for the appropriate response peers in social-like p2p networks. Second, this study designs a novel knowledge index mechanism that dynamically adapts social relationship p2p networks. The results show that the proposed social relationship p2p network improves search performance significantly, compared with existing approaches.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1153-1159
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• 2014

In this paper we propose novel method for cost of harbor facility of redevelopment of Mookho harbor at Donghae city by using ICT(Information Communication Technology) and Social Network System that is able to participate most residents instead of partly participation for harbor development. In order to do this, we analyze urban marketing which was maximally reflected opinion of resident by using previous simple questionnaire as well as various SNS (Social Network System) as method of effective resident's participation in process harbor redevelopment. We perform optimal selection for ratio of resident's participation. We also propose calculation of optimal construction cost and method of urban marketing.

• Journal of Distribution Science
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• v.14 no.8
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• pp.35-44
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• 2016

Purpose - This study aims to understand the relationship between Chinese local SNS usage and social capital building through Chinese international students in South Korea. A research model that illustrates the relationship between the SNS usage (i.e., intensity, communication and social capital building is proposed. Based on the analysis, this study will provide responses to the question of if SNS really presents the danger of trapping international consumers in their local comfort zone or enhance social capital for the users. Research design, data, and methodology - The survey questionnaire is circulated among the WeChat (a Chinese local SNS) users who are the Chinese international students studying in South Korea. The collected data is analyzed by structural equation method using SPSS and AMOS. Results - Proposed hypotheses of the positive relationships between the attachment of SNS use and both individuals' bridging and bonding social capital are supported. It's also supported that (1) interpersonal communication, (2) interpersonal communication with old friends, and (3) interpersonal communication for making new friends on SNS positively influence individuals' bridging social capital. Conclusions - This paper demonstrates the importance of intensity of WeChat use and interpersonal communication that impact Chinese international students' bridging and bonding social capital on WeChat.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.527-530
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• 2011

This Paper studied out prototype and the structure of comic expression on Social Network Game and started with issues based on SNS(Social Network Service) in Culture Communication. Interaction with the platform have the information that aims to develop relationships with SNG. In a world where the paradigm is changing the game People of all ages, transcending national borders in the mediator role of interaction could have been important. Today SNG is a major topic in Game Contents and this issue has influenced the game design and Story Telling. Under this Situation, this study has a significant meaning because it proves that the factors Comic Expression in game is analyzed by SNG.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.18-26
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• 2011

Social network services whose users increase rapidly is the online services that reflect social network. They are used for various purposes such as strategy of election, commercial advertisement and marketing, educational information sharing and exchange of medical knowledge and opinions. These services make users form social networks with other users who have common interests and expand their relationships by releasing their personal information and utilizing other users' social networks. However, the social network services based on open and sharing of information raise various security threats such as violation of privacy and phishing. In this paper, we propose a group key management scheme and protocols using key rings to protect communication of small groups in social network services.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.797-804
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• 2017

A social network is a typical social science environment with both network and iteration characteristics. This research presents a reaction analysis model of how each node responds to social networks when given input such as promotions or incentives. In addition, the setting value of a specific node is changed while examining the response of each node. And we try to understand the reactions of the nodes involved. The reaction analysis model is constructed by applying various techniques such as unidirectional, fuzzy set, weighting, and cyclic feedback, so it can accommodate the complicated environment of practice. Finally, the implementation model is implemented using Vensim rather than NetLogo because it requires repetitive input, change of setting value in real time, and analysis of association between nodes.