• Asia pacific journal of information systems
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• v.23 no.3
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• pp.105-129
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• 2013

This study draws important factors in electronic Word-of-Mouth (eWOM) and examines how these influence the building of customer loyalty. eWOM is viewed as social communication between customers and sellers, and thus the communicative action theory is applied. With the theory, we identify reviewer and seller as influential players on customers, and derive important factors such as correctness and veracity of reviews from the reviewers' action, and information compactness and adequacy from the seller's action. We propose these constructs as antecedents of customer loyalty and further hypothesize their curvilinear impacts as follows: the marginal impacts of veracity and correctness will decrease as veracity and correctness increase, and the marginal impacts of compactness and adequacy will increase as compactness and adequacy increase. The result indicates that only the seller's action has a curvilinear impact, whereas the reviewer has proportional positive impact on customer loyalty. This study indentifies important factors in eWOM from a critical social theory perspective and validates them using the positivistic approach. For practitioners, it discusses the important factors in eWOM with the identification of the individuals who are responsible for these factors.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.218-223
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• 2021

The five elements of big data are said to be Volume, Variety, Velocity, Veracity, and Value. Among them, data lacking the Veracity of the data or fake data not only makes an error in decision making, but also hinders the creation of value. This study analyzed YouTube's revenue structure to focus the effect of data integrity on data valuation among these five factors. YouTube is one of the OTT service platforms, and due to COVID-19 in 2020, YouTube creators have emerged as a new profession. Among the revenue-generating models provided by YouTube, the process of generating advertising revenue based on click-based playback was analyzed. And, analyzed the process of subtracting the profits generated from invalid activities that not the clicks due to viewers' pure interests, then paying the final revenue. The invalid activity in YouTube's revenue structure is Raw Data, not pure viewing activity of viewers, and it was confirmed a direct impact on revenue generation. Through the analysis of this process, the new Data Value Chain was proposed.

• Journal of Periodontal and Implant Science
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• v.50 no.4
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• pp.207-208
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• 2020

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.265-274
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• 2017

This paper examines the problems of big data analysis education and suggests ways to solve them. Big data is a trend that the characteristic of big data is evolving from V3 to V5. For this reason, big data analysis education must take V5 into account. Because increased uncertainty can increase the risk of data analysis, internal and external structured/semi-structured data as well as disturbance factors should be analyzed to improve the reliability of the data. And when using opinion mining, error that is easy to perceive is variability and veracity. The veracity of the data can be increased when data analysis is performed against uncertain situations created by various variables and options. It is the node analysis of the textom(텍스톰) and NodeXL that students and researchers mainly use in the analysis of the association network. Social network analysis should be able to get meaningful results and predict future by analyzing the current situation based on dark data gained.

• Journal of Wetlands Research
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• v.18 no.1
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• pp.100-112
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• 2016

In recent, the direction of water resources policy is changing from the typical plan for water use and flood control to the sustainable water resources management to improve the quality of life. This change makes the information related to water resources such as data collection, management, and supply is becoming an important concern for decision making of water resources policy. We had analyzed the structured data according to the purpose of providing information on water resources. However, the recent trend is big data and cloud computing which can create new values by linking unstructured data with structured data. Therefore, the trend for the management of water resources information is also changing. According to the paradigm change of information management, this study tried to suggest an application of big data and cloud computing in water resources field for efficient management and use of water. We examined the current state and direction of policy related to water resources information in Korea and an other country. Then we connected volume, velocity and variety which are the three basic components of big data with veracity and value which are additionally mentioned recently. And we discussed the rapid and flexible countermeasures about changes of consumer and increasing big data related to water resources via cloud computing. In the future, the management of water resources information should go to the direction which can enhance the value(Value) of water resources information by big data and cloud computing based on the amount of data(Volume), the speed of data processing(Velocity), the number of types of data(Variety). Also it should enhance the value(Value) of water resources information by the fusion of water and other areas and by the production of accurate information(Veracity) required for water management and prevention of disaster and for protection of life and property.

• Knowledge Management Research
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• v.24 no.1
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• pp.51-72
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• 2023

Digital literacy is vital knowledge and ability of an individual in the information society. As the level of digital literacy increases, the interest in privacy protection increases. This change may hinder the use of digital technologies and services. This research examines (1) the mediating effect of online social participation and information veracity on smart device literacy and privacy concerns, and (2) the moderating effect of privacy literacy. Using Korean media panel survey data reported in 2020 and in 2021, this study analyzes the responses of 7,737 people who use smart devices and participate in online activities. SPSS and PROCESS Macro are used to test the research model and hypotheses. In the analysis of 2020 and 2021 survey, this research shows that smart device literacy has major effects on privacy concerns; confirms that the mediating effect of online social participation; moderated meditating effect of privacy literacy. Although information veracity is not significant in 2020, mediating and moderated mediating effects are found in 2021.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.413-414
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• 2019

빅데이터는 초기에는 개념적인 접근으로 대용량의 데이터로 정의하기도 하였으나 지금은 데이터를 수집, 저장, 처리, 분석하여 가치 창출까지의 개념으로 확산되고, 최근에는 정확성(Veracity), 가변성(Variability), 시각화(Visualization) 개념까지 새롭게 추가되어 7V로 제시되기도 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3868-3888
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• 2022

A widely used social networking service like Twitter has the ability to disseminate information to large groups of people even during a pandemic. At the same time, it is a convenient medium to share irrelevant and unverified information online and poses a potential threat to society. In this research, conventional machine learning algorithms are analyzed to classify the data as either non-rumor data or rumor data. Machine learning techniques have limited tuning capability and make decisions based on their learning. To tackle this problem the authors propose a deep learning-based Rumor Detection Neural Network model to predict the rumor tweet in real-world events. This model comprises three layers, AttCNN layer is used to extract local and position invariant features from the data, AttBi-LSTM layer to extract important semantic or contextual information and HPOOL to combine the down sampling patches of the input feature maps from the average and maximum pooling layers. A dataset from Kaggle and ground dataset #gaja are used to train the proposed Rumor Detection Neural Network to determine the veracity of the rumor. The experimental results of the RDNN Classifier demonstrate an accuracy of 93.24% and 95.41% in identifying rumor tweets in real-time events.

• Korean Journal of Forensic Psychology
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• v.12 no.1
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• pp.53-73
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• 2021

This study is an experimental study comparing the psycho-physiological response differences of subjects according to the rapport building in polygraph tests. We randomly assigned 84 adults into a 2(veracity: Truth vs. Lie) x 2(rapport; Rapport building vs. Non-rapport building) between-subject design and measured ESS total scores as psycho-physiological responses. In order to manipulate the veracity conditions, participants in the truthful condition were told to tell their actual scores on several simple tasks but those in the lie condition were asked to tell higher scores than their actual scores. Afterwards all participants were polygraph tested in the order of pre-interview and main examination. The rapport conditions were manipulated by structured pre-interview scripts. As a result, there were significant differences in the examinee's total ESS scores depending on the veracity and rapport conditions. For truth-tellers, the ESS total scores were greater in the positive(+) direction in the rapport building condition than in the non-rapport building condition, indicating a prominent true response in the former condition. For liars, however, the ESS total scores were not significantly greater in the negative(-) direction in the rapport building condition than in the non-rapport building condition. Based on this study's results, we discussed the importance of rapport building in the pre-interview phase of a polygraph test and the need to operationalize verbal and non-verbal rapport building techniques.

• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.16-24
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• 2020

The study empirically explored factors influencing How storytelling factors in social networking services, SNS, affect consumer response on the uses and gratification theory. conducted an analysis of 120 university students attending universities in the Seoul metropolitan area using an experiment. The results of this study are as follows: first, The storytelling factors, relevance and veracity have a positive effect on clarity. second, it has been shown that only veracity has a positive effect on parai-social interaction with media figures with emotional attachment. third, para-social interactions have been shown to influence content attitudes and orality sequentially. This study deals with the effect of SNS storytelling on the consumer's part, providing practical implications for enhancing content attitudes and word-of-mouth, by increasing para-social interactions with consumers while identifying the components that should enhance the way SNS is delivered in terms of storytelling.