• Journal of Distribution Science
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• 제14권10호
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• pp.165-178
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• 2016

Purpose - This study aims to empirically verify the impact of media richness, social presence, and prior life satisfaction on various continual usage or withdrawal behaviors of SNS users via both a positive path of satisfaction and a negative path of relative deprivation. By identifying these causal paths, we observe dynamic interactions of SNS user psychology in a balanced view, and provide some implications about design principles for SNS providers. Research design, data, and methodology - We developed 16 hypothesis based on media richness theory, social presence theory, social comparison theory, the literature about relative deprivation, and the literature about the various reactions of IS users. The rich SNS media, social presence recognition among peer SNS users, and prior life satisfaction could generate positive experience, attitude, and virtuous behavioral intentions among SNS users. At the same time, rich media, low social presence, and low prior life satisfaction could generate relative deprivation and could increase withdrawal behavioral intentions such as refusal to provide information, misrepresentation of information, and removal of uploaded information in SNS. Scenario surveys were conducted to collect data from potential SNS users. Data from 357 surveys were collected and analyzed through a PLS algorithm to test the hypotheses. Results - Media richness, social presence, and prior life satisfaction could significantly increase perceived enjoyment, satisfaction, and behavioral intention of continual usage and knowledge sharing. They also could significantly decrease refusal and misrepresentation intention. Relative deprivation is significantly decreased only by prior life satisfaction. Relative deprivation could not significantly decrease satisfaction, but it could significantly increase misrepresentation and removal intention, which could be regarded as information distortion intention. Conclusions - SNS providers should focus on developing rich media and social presence support because these two variables could impact the positive experiences of SNS users. Moreover, the positive experiences could heavily influence SNS user behavior. Some management is needed to prevent relative deprivation and its consequences of misrepresentation and removal intention. SNS providers should prevent SNS users from excessive image misrepresentation and removal as this information distortion could be the source of relative deprivation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제12권6호
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• pp.267-272
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• 2012

IT convergence, social media, and the companies' customer service industry advancement, data collection activities, explosion of multimedia content with increased smartphone penetration, SNS activation networks to expand the pool of things, 10 years ago, the amount of data eunneun evenly across industries, EDW (Enterprisehad increased the demand for the Data Warehouse).Recent proliferation of SNS users and applied research background with Big Data as a new study is proposed to proceed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.3203-3215
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• 2015

Due to the high growth of SNS population, service scalability is one of the critical issues to be addressed. The cloud environment provides the flexible computing and storage resources for services deployment, which fits the characteristics of scalable SNS deployment. However, if the SNS related information is not properly placed, it will cause unbalance load and heavy transmission cost on the storage virtual machine (VM) and cloud data center (CDC) network. In this paper, we characterize the SNS into a graph model based on the users' associations and interest correlations. The node weight represents the degree of associations, which can be indexed by the number of friends or data sources, and the link weight denotes the correlation between users/data sources. Then, based on the SNS graph, the two-step algorithm is proposed in this paper to determine the placement of SNS related data among VMs. Two k-means based clustering schemes are proposed to allocate social data in proper VM and physical servers for pre-configured VM and dynamic VM environment, respectively. The experimental example was conducted and to illustrate and compare the performance of the proposed schemes.

• Journal of information and communication convergence engineering
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• 제17권4호
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• pp.239-245
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• 2019

Recently, effort to obtain various information from the vast amount of social network services (SNS) big data generated in daily life has expanded. SNS big data comprise sentences classified as unstructured data, which complicates data processing. As the amount of processing increases, a rapid processing technique is required to extract valuable information from SNS big data. We herein propose a system that can extract human sentiment information from vast amounts of SNS unstructured big data using the naïve Bayes algorithm and natural language processing (NLP). Furthermore, we analyze the effectiveness of the proposed method through various experiments. Based on sentiment accuracy analysis, experimental results showed that the machine learning method using the naïve Bayes algorithm afforded a 63.5% accuracy, which was lower than that yielded by the NLP method. However, based on data processing speed analysis, the machine learning method by the naïve Bayes algorithm demonstrated a processing performance that was approximately 5.4 times higher than that by the NLP method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• 제8권6호
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• pp.544-550
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• 2015

The opinion mining technique which analogize significant information from SNS message is increasingly important because opinions communicated through SNS are increasing. This paper propose SEIAS(SNS Emotional Information Analysis Strategy) based on opinion mining that analogize emotional information from SNS setting a different weight according to position of antonym and adverb. Firstly, the proposed SEIAS constructs a emotion dictionary for opinion mining analysis, Secondly, it collects SNS data on real time, compare it with emotion dictionary and calculates opinion value of SNS data. Specially, it increases the precision of opinion analysis result compared to the existing SO-PMI because it sets up the different value according to the position of antonym and adverb when it calculates the opinion value of data.

• The KIPS Transactions:PartC
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• 제18C권4호
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• pp.217-226
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• 2011

As a diverse range of smartphones has been recently developed and diffused, the users of SNS (Social Network Service) also have been sharply increased. The SNS saves a variety of information such as exchanged pictures and videos, voice mails or location sharing, chat history, etc. as well as simple user data, so that the acquisition of data that are useful in the aspect of digital forensic is achievable. This thesis reviews the types of SNS that are available for the iPhone, a recent example of highly used smartphones, and types of data by each client. Also, efficient data analysis method for digital forensic investigations is suggested by analyzing the relationships within the collected data by each client.

• Journal of Information Technology Applications and Management
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• 제19권4호
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• pp.75-95
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• 2012

This study focuses on examining the determinants of smartphone-based social network services(SNS) use. That is, the study explores the key factors affecting the use of smartphone-based SNS. People who have been using online-based SNS such as Cyworld and Facebook for years are now using mobile-based SNS such as KakaoStory. Under the situation. the study attempts to draw key determinants of smartphone-based SNS use from the studies of TAM, hedonic information systems, and social perspectives. To test the hypotheses, we conducted partial least squares (PLS) analysis using a total of 233 data collected on the users of smartphone-based SNS including KakaoTalk and KakaoStory. The key findings are as follows : first, it is verified that both ease of use and usefulness, two main factors in TAM, had positive effects on smartphone-based SNS use. Second, for enjoyment and escapism considered as the two main factors of hedonic IS characteristics, only the effect of enjoyment on SNS use was significant. Finally, social ties as a factor of social characteristics had the most significant effect on smartphone-based SNS use. The result implies that smartphone-based SNS can be one of the major means of maintaining existing social ties.

• Journal of Fisheries and Marine Sciences Education
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• 제26권5호
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• pp.1138-1150
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• 2014

The Purpose of this study was conducted to investigate the factors influencing SNS addiction among university students for providing the basic data to develop SNS addiction prevention program. The data were collected from 363 university students in B & K cities from 2 to 19 September, 2013 and analyzed with t-test, ANOVA and multiple regression by using SPSS 21.0 program. The significant factors of SNS addiction were average using time daily in weekend(${\beta}=.116$, p=.003), SNS using time per connect(${\beta}=.156$, p=<.001), communication motive(${\beta}=.214$, p<.001), non-loneliness motive(${\beta}=.114$, p=.010), social capital(${\beta}=.127$, p=.001), psychological problems(${\beta}=.381$, p<.001). And these factors explained 54.2% of the variance in SNS addiction. In conclusion, the results from this study indicated a need to develop the intervention program to prevent SNS addiction for health promotion of university students.

• Journal of Korean Society for Quality Management
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• 제46권2호
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• pp.339-350
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• 2018

Purpose: The purpose of this study is to propose useful suggestions by analyzing the impact of SNS quality and the pressure which comes from SNS usage objectives on SNS discontinuance intention. Methods: We developed a SNS user's discontinuance intention model in terms of SNS quality and pressure of SNS usage. Survey data of SNS users was analyzed using multi-regression analysis for testing hypotheses. Results: We found that information quality plays an important role in lowering the SNS discontinuance intention. In addition, it was founded that pressure of social networking and information processing are positively related with the SNS discontinuance intention. Conclusion: We expect that this research can provide theoretical and practical implications. As for theoretical, this study can suggest the insight on conceptualization of SNS fatigue in the further study. Regarding practical implication, service providers can make their service strategies based on understanding our analysis.

• Journal of Digital Convergence
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• 제11권5호
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• pp.41-51
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• 2013

A lots of social data are distributed, utilized and opened through the social media. They have characterized effectiveness and pleasure of information to the media by social data but it is ignored about excessive exposure of information and damage from collective reply of personal attack type. In this paper, we study about analysis of opinion social data on the SNS (Social Network Service) by analyzing of collective damage reply. It is analysed by diverse measurement method for distribution and disuse of the amount of Buzz data that is analysed data from structured social network.