• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.121-131
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• 2017

With emergence of Internet, social media, and mobile service, the consumers have actively presented their opinions and sentiment, and then it is spreading out real time as well. The user-generated text data on the Internet and social media is not only the communication text among the users but also the valuable resource to be analyzed for knowing the users' intent and sentiment. In special, economic participants have strongly asked that the social big data and its' analytics supports to recognize and forecast the economic trend in future. In this regard, the governments and the businesses are trying to apply the social big data into making the social and economic solutions. Therefore, this study aims to reveal the capability of social big data analysis for the economic use. The research proposed a social big data analysis model and an online consumer sentiment index. To test the model and index, the researchers developed an economic survey ontology, defined a sentiment dictionary for sentiment analysis, conducted classification and sentiment analysis, and calculated the online consumer sentiment index. In addition, the online consumer sentiment index was compared and validated with the composite consumer survey index of the Bank of Korea.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.101-108
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• 2015

This paper presents the implementation of a system that recommends empirical best routes based on classification of large trajectory data. As many location-based services are used, we expect the amount of location and trajectory data to become big data. Then, we believe we can extract the best empirical routes from the large trajectory repositories. Large trajectory data is clustered into similar route groups using Hadoop MapReduce framework. Clustered route groups are stored and managed by a DBMS, and thus it supports rapid response to the end-users' request. We aim to find the best routes based on collected real data, not the ideal shortest path on maps. We have implemented 1) an Android application that collects trajectories from users, 2) Apache Hadoop MapReduce program that can cluster large trajectory data, 3) a service application to query start-destination from a web server and to display the recommended routes on mobile phones. We validated our approach using real data we collected for five days and have compared the results with commercial navigation systems. Experimental results show that the empirical best route is better than routes recommended by commercial navigation systems.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.12
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• pp.301-312
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• 2018

In industrial wireless sensor networks, the continuous object detection such as fire or toxic gas detection is one of major applications. A continuous object occurs at a specific point and then diffuses over a wide area. Therefore, many studies have focused on accurately detecting a continuous object and delivering data to a static sink with an energy-efficient way. Recently, some applications such as fire suppression require mobile sinks to provide real-time response. However, the sink mobility support in continuous object detection brings challenging issues. The existing approaches supporting sink mobility are designed for individual object detection, so they establish one-to-one communication between a source and a mobile sink for location update. But these approaches are not appropriate for a continuous object detection since a mobile sink should establish one-to-many communication with all sources. The one-to-many communication increases energy consumption and thus shortens the network lifetime. In this paper, we propose the origin-centric communication scheme to support sink mobility in a continuous object detection. Simulation results verify that the proposed scheme surpasses all the other work in terms of energy consumption.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.77-88
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• 2021

Cloud computing is getting a lot of attention by many people and businesses due to IT environmental changes such as the proliferation of smart devices, the increase of digital data, and the cost of IT resources. More individuals use personal cloud computing services for storing and managing information and data. Therefore, this study proposed determinants that are expected to have an influence on evaluating the value of cloud computing based on the value-based adoption model, examining the relationship between the continuous use intention of cloud computing. Results of the study show that usefulness, convenience of information access, extensibility had a positive impact on perceived value while privacy concerns and costs had a negative impact on perceived value. In addition, perceived value was found to have a significant effect on the intention to continue use of cloud computing. Finally, trust was found to have a significant effect on the perceived value and the intention to continue use of cloud computing. The findings are expected to provide useful information for understanding the factors that individual users consider important in the steadily growing cloud computing market.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.410-419
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• 2016

This study examined the satisfaction difference in the aspects of awareness, information quality, and availability in healthcare applications according to smartphone user's characteristics. Data collection was conducted between September 17th and September 21st 2014 on the 193 people who had used healthcare applications, and the data collected were analyzed with descriptive statistics, t-test, One-way ANOVA, and Kruskal-Wallis test using SPSS WIN 20.0. Differences in satisfaction of healthcare application were observed according to the general characteristics, and according to age, education level, and income, as well as for healthcare application use characteristics, according to operation system, total use period, the number of installed healthcare applications, the sources of main information, use frequency, and reasons of no use. To establish strategies for the effective spread of mobile healthcare and development and distribution of healthcare applications, it will be necessary to confirm smartphone users' characteristics and it is important to reflect them in the strategies. In addition, it is necessary to develop and implement a range of strategies to ceaselessly induce the users' motives of use and to improve their degree of satisfaction to secure the constant use of developed health care applications.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.89-102
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• 2014

Since the Arab spring in 2010, SNS prompted discussions about the roles to organize collective actions. First of all, mobile media and SNS help to mobilize both on and offline social movement, second, to create new forms of collective actions, third, to organize social movement organizations across the world, fourth, to empower movement participants to develop new collective identities. On the other hand, the same technologies also hinder social movements from developing continuity and dedication. In addition, the problems of digital divide might aggravate the divisive process to organize collective actions across the world. This research is built on these ongoing arguments about the potentials and limitations of new media technologies. In particular, this research tries to move beyond the confrontational approaches to the media through the case study of Save The Jeju Island social movements on Facebook. The movement SNS on Facebook aims to provide as well as organize international SMOs and activists that might help deeper understandings on the potentials and limitations of online communication strategies for global social movements.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.11
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• pp.393-402
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• 2014

We have experienced an explosive increase of the IoT(Internet of Things) technology based devices including smart phones and the wireless communications. Also the growing power consumption in IEEE 802.11 WLANs(Wireless LANs) driven by these dramatic increases in not only mobile users and but also wireless APs(Access Points). To reduce the power consumption, this paper proposes a wireless AP power saving algorithm, which minimizes the transmission power without decrease the transmission and carrier sense ranges. A wireless AP which is use in our algorithm checks its own original coverage periodically for whether there is a new STA(Station) or not when its transmission power is decreased. Moreover, if there are no signaling message to connect the wireless AP, it changes its operation mode Wake-up to sleep. A Result shows that the proposed AP algorithm can reduce the total power consumption of the wireless AP approximated 18% and 35% compared to the conventional wireless AP with and without the existing power saving algorithm, respectively.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.69-90
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• 2023

The purpose of this study is to evaluate the service attributes and consumer reactions of telemedicine apps in South Korea and visualize their differentiation by constructing positioning maps. We crawled 23,219 user reviews of 6 major telemedicine apps in Korea from the Google Play store. Topics were derived by BERTopic modeling, and sentiment scores for each topic were calculated through KoBERT sentiment analysis. As a result, five service characteristics in the application attribute category and three in the medical service category were derived. Based on this, a two-dimensional positioning map was constructed through principal component analysis. This study proposes an objective service evaluation method based on text mining, which has implications. In sum, this study combines empirical statistical methods and text mining techniques based on user review texts of telemedicine apps. It presents a system of service attribute elicitation, sentiment analysis, and product positioning. This can serve as an effective way to objectively diagnose the service quality and consumer responses of telemedicine applications.

• Knowledge Management Research
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• v.25 no.2
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• pp.115-134
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• 2024

In an age where consumers can easily search and pass on their opinions of products and purchasing decisions through the internet, Electronic-word-of-mouth(Ewom) plays an important role in decision making of other potential customers. In this study, we empirically analyze the impact EWOM on consumer purchase decisions, when contradictory Ewom is presented from varying sources of information, such as experts and general consumers. First, we find that when there is a consensus among different information sources there exists a positive relationship between Ewom sentiment and purchase intent, confirming the results of previous literature. However, when expert opinion and consumer opinion do not match we find that consumer opinion is more impactful on purchasing decisions compared to the expert opinion, regardless of product types. The findings of this study add insight to the current literature by examining the effect of contradictory Ewom on purchase decisions, and also to industry marketers by presenting a more efficient strategy in promoting positive Ewom for different product types.

• Korean Security Journal
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• no.62
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• pp.35-63
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• 2020

As the frequency and intensity of catastrophic disasters increase, there is widespread public sentiment that government capacity for disaster response and recovery is fundamentally limited, and that the involvement of civil society and the private sector is ever more vital. That is, in order to strengthen national disaster response capacity, governments need to build disaster systems that are more participatory and function through the channels of civil society, rather than continuing themselves to bear sole responsibility for these "wicked problems." With the advancement of smart mobile technology and social media, government and society as a whole have been called upon to apply these new information and communication technologies to address the current shortcomings of government-led disaster management. As illustrated in such catastrophic disasters as the 2011 Tohoku earthquake and tsunami in Japan, the 2010 Haitian earthquake, and Hurricane Katrina in the United States in 2005, the realization of participatory potential of smart technologies for better disaster response has enabled citizen participation via new smart technologies during disasters and resulted in positive impact on the management of such disasters. In this context, this study focuses on the South Korean context, and aims to analyze Korean government officials' readiness for public participation using smart technologies. On this basis, it aims to offer policy suggestions aimed at promoting smart technology-enabled citizen participation. For this purpose, it proposes a particular model, termed SMART (System, Motivation, Ability, Response, and Technology).