• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.267-276
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• 2017

Damages have occurred in various fields such as agriculture, industry, and citizen's health due to the yellow dust. Therefore, it is urgent to take measures against it. In this regard, this study collected data of yellow dust over 11 days on a basis of Feb. 23. 2015 when yellow dust was the greatest after 2009, issue words analysis and recomposed health related tweet data. After testing the significance of yellow dust related diseases by association rule analysis with diseases, it obtained the study results as follows: As a result of significance test for the patients with rhinitis, asthma and conjunctivitis by acquiring the condition data of patients from the Health Insurance Review & Assessment Service, conjunctivitis appeared to be significant in 13 cities for 16 cities at 5% significance probability, while asthma and rhinitis showed a significance in 3 and 6 areas. As described above, it is possible to obtain information about citizens' health from SNS data, such as Tweet data and it is judged that these data will provide useful information for establishing measures of citizens' health care.

• Korean journal of communication and information
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• v.58
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• pp.7-30
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• 2012

The advent of Social Journalism coincided with the rise of social media to create and deliver news information; as a type of civic journalism, social journalism may be characterized as a new form of information gathering and news reporting which is fed by citizens creating news information through their use social networking services (SNSs). The current study analyzed a Facebook page called, to determine how this page was utilized during the onset of the citizen movement for the Egyptian democratic revolution to produce news, to facilitate interaction among the public and to deliver the news under the form of networked journalism. Each post uploaded onto the Facebook page from January 27 till February 2, 2011 was coded in its category, content and the contextual frame of the news. The results of the study showed that during the first week, straight news rather than those with opinions was produced most frequently. The research findings of the current study suggest that in a society of political turmoil, such as in Egypt and other Arabic countries, when the institutionalized media are controlled severely by the government or other forces, SNSs can perform journalistic media roles which create and distribute news information representing facts and reality, and simultaneously facilitate the public's interactions on social and political issues.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.48-56
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• 2012

One kind of crowdsourcing techniques which allow drivers to collect and provide traffic information using smartphones and applications is being introduced to ITS system as well. The introduction of crowdsourcing techniques requires changes in the existing ITS based on Insourcing which provide traffic information generated by detectors through VMS. ITS Information have had two problems, one is the high cost and the other is an interrupted service. Experts expect crowdsourcing technique which is created SNS, will overcome problems of ITS. But, there are not many examples and research results. Crowdsourcing technique was utilized in Jeju ATMS project to install ITS on the coastal round roads around Jeju since ITS to install point detectors turned out to be non-economic method in case of the coastal round roads with low traffic volume. However, there existed links in which traffic information cannot be generated as there were no smartphone users (crowds) even in the cost-effective crowdsourcing techniques, which indicates the fact that the crowdsourcing method is suitable for urban roads with many smartphone users, but not for local minor roads. On the contrary, insourcing-based ITS is considered to be non-economic method in applying to all roads in the city, but it can be effectively utilized in the local minor roads. Accordingly, Inter-sourcing based ITS operating system in which insourcing is connected with crowdsourcing was suggested in this study.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.163-171
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• 2016

This study derived the policy implications and market strategies by analysis the e-book companies requirements & the CPND value chain structure, in order to revitalize the e-book market in Korea. Specifically, we examined the prospect of e-book market in Korea, current situations of production and distribution, awareness of service utilization and requirements for support policy with targets of 30 companies. As a research, the most needed item for e-book companies is 'PR and marketing support to enter and open the markets'(27%), which is the highest. 'Financial support such as labor costs and business expenses', 'support for retraining personnel to develop the expertise in respective fields' are followed and they account for 22%. Currently, the most effective support item is the external support program(35%) and funding power(30%) is followed. Unlike a paper book market, e-book is turned into a platform business in terms of the value chain. Based on these research content, e-book market activation and corporate competitive strategy was derived as follows : 1)literacy reinforcement about SNS marketing and e-pub3 authoring tool. 2)statistical DB construction of retail sales channels. 3)diversification of the billing system. 4)The quality of the e-book content certification.

• Journal of The Korean Association For Science Education
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• v.35 no.5
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• pp.829-840
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• 2015

In this study, we analyzed the teaching practices of science teachers using smart technologies and investigated their difficulties in implementing smart education and their educational needs. We also studied their opinions on the application of smart technologies in science education. The participants were seven science teachers who participated in the smart education study group of a science teacher association in Seoul. We elaborated on the characteristics of smart education in science education during comprehensive analyses of instructional materials used in science classes and the initial interviews. We then analyzed the second interviews by categorizing their responses inductively. All the science teachers used the 'instant access as needed', but their interactions, simply answering students' questions, were found to be at a low level. They did not effectively use the 'collaborative interaction with SNS or wiki-based service' for the support for interactive learning. While most collected learning results of their students and provided feedback in the aspect of 'individualization according to leaner level', they were not aware of 'context, situation, and location of learners' in smart education. While all the teachers extended learning opportunities by using learning resources widely in smart education, most were not aware of 'support for self-directed learning'. Most teachers believed that smart education should be developed to help students learn interactively and in a self-directed manner. They also provided many opinions on teacher training programs and environmental support for smart education. Based on the results, some considerations for implementing smart education in science instructions effectively are discussed.

• The Journal of Society for e-Business Studies
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• v.21 no.3
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• pp.15-28
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• 2016

This paper proposes a system recommending spatial information what user wants with collecting and analyzing tweets around the user's location by using the GPS information acquired in mobile. This system has built an emotion dictionary and then derive the recommendation score of morphological analyzed tweets to provide not just simple information but recommendation through the emotion analysis information. The system also calculates distance between the recommended tweets and user's latitude-longitude coordinates and the results showed the close order. This paper evaluates the result of the emotion analysis in a total of 10 areas with two keyword 'Restaurants' and 'Performance.' In the result, the number of tweets containing the words positive or negative are 122 of the total 210. In addition, 65 tweets classified as positive or negative by analyzing emotions after a morphological analysis and only 46 tweets contained the meaning of the positive or negative actually. This result shows the system detected tweets containing the emotional element with recall of 38% and performed emotion analysis with precision of 71%.

• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.142-151
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• 2020

The reason why today's public actively uses social communication is that the necessary information is collected and classified under the name of social big data through the web space to create the big data era, an ecosystem of information. In order for big data information to be used by the public, it is necessary to visualize it easily. This study categorized the types of visualization according to the information of social big data, and targeted the experienced students including the related majors and the general public who need to directly utilize and study the actual big data visualization as an experience evaluation target. As a result of analyzing the experiences of the experienced people, important implications for the visualization method for managing, analyzing, and utilizing the data were derived. The big data visualization strategy is to be expressed in a way that fits the data environment and user's eye level on SNS. In the future, if big data visualization is applied to product service or social trend, it will be an important data in terms of broadening its role, scope of application, and application.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.11-21
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• 2010

To aim at improving performance and reflecting user's needs of retrieval, the number of researches has been actively conducted in recent year as the quantity of information and generation of the web pages exceedingly increase. One of alternative approaches can be a tagging system. It makes users be able to provide a representation of metadata including writings, pictures, and movies etc. called tag and be convenient in use of retrieval of internet resources. Tags similar to keywords play a critical role in maintaining target pages. However, they still needs time consuming labors to annotate tags, which sometimes are found to be a hinderance caused by overuse of tagging. In this paper, we present an automatic tagging scheme for a solution of current tagging system conveying drawbacks and inconveniences. To realize the approach, face recognition-based tagging system on SNS is proposed by building a face area detection procedure, linear-based classification and boosting algorithm. The proposed novel approach of tagging service can increase possibilities that utilized SNS more efficiently. Experimental results and performance analysis are shown as well.

• Journal of Distribution Science
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• v.14 no.4
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• pp.47-53
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• 2016

Purpose - The objective of this study is to investigate the dynamic relationships among Advertising Cost (AD), Newly Registered Users(NRU), and Buying Users(BU) of Social Network Game(SNG). SNG is getting pervasive mainly due to the rapid growth of mobile game and Social Network Service(SNS). It would be helpful for marketing researchers interested in SNG and related practitioners to understand the changes in AD, NRU, and BU with time as well as the effects on one another in mutual and dynamic way. Research Design, Data, and Methodology - Necessary data were collected from Social Network Game(SNG) company. AD, NRU, and BU are endogenous variables, but new event such as launching (event) and holidays(holiday) are exogenous dummy variables. Vector Auto regression (VAR) model is generally used to examine and capture the dynamic relationships among endogenous variables. VAR model can easily capture dynamic and endogenous relationships among time-series variables. Vector Auto regression with Exogenous variables(VARX) is a model in which exogenous variables are added to VAR. To investigate this study, VARX is applied. Result - By estimating the VARX model, the author finds that the past periods' NRU affect negatively and significantly the present AD, and past periods' BU have a positive and significant impact on the increase of AD. In addition, the author shows that the past periods' AD and BU have a positive and significant effect on the increase of NRU, and the past periods' AD affect positively and significantly BU. While the impact of AD on NRU happens after 3 or 4 days (carryover effect), that of AD on BU comes about within just 1 or 2 days (immediate effect). The effect of BU on NRU can be considered as word of mouth (WOM effect). Therefore, SNG companies can obtain not only the growth of revenue but also the increase of NRU by increasing BU. Through those results, the author can also find that there are significant interactions between endogenous variables. Conclusion - This study intends to investigate endogenous and dynamic relationships between AD, NRU, and BU. They also give managerial implications to practitioners for SNS and SNG firms. Through this study, it is found that there exist significant interactions and dynamic relationships between those three endogenous variables. The results of this study can have meaningful implications for practitioners and researchers of SNG. This research is unique in that it deals with "actual" field data and intend to find "actual" relationships among variables unlike other related existing studies which intend to investigate psychological factors affecting the intention of game usage and the intention of purchasing game items. This study is also meaningful by showing that the increase of BU can be a good strategy for "killing birds with one stone" (i.e., revenue growth and NRU increase). Although there are some limitations related with future research topics, this research contributes to the current research on SNG marketing in the above mentioned ways.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.97-105
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• 2023

Recently, with the development of artificial intelligence technology, many technologies for user convenience are being developed. Among them, interest in autonomous vehicles is increasing day by day. Currently, many automobile companies are aiming to commercialize autonomous vehicles. In order to lay the foundation for the government's new and reasonable policy establishment to support commercialization, we tried to analyze changes and perceptions of public opinion through news article data. Therefore, in this paper, 35,891 news article data mentioning terms similar to 'autonomous vehicles' over the past three years were collected and network analyzed. As a result of the analysis, major keywords such as 'autonomous driving', 'AI', 'future', 'Hyundai Motor', 'autonomous driving vehicle', 'automobile', 'industrial', and 'electric vehicle' were derived. In addition, the autonomous vehicle industry is developing into a faster and more diverse platform and service industry by converging with various industries such as semiconductor companies and big tech companies as well as automobile companies and is paying attention to the convergence of industries. To continuously confirm changes and perceptions in public opinion, it is necessary to analyze perceptions through continuous analysis of SNS data or technology trends.