• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.149-156
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• 2021

Gambling negatively affects the economy, and it brings unwanted financial, social, and health outcomes to gamblers. On the one hand, unemployment is argued to be a leading cause of gambling. On the other hand, gambling can cause unemployment in the second-order via gambling-induced poor health, falling productivity, and crime. In terms of significant effects, previous studies were able to establish an association, but not causality. The current study examines the time-sequence and contemporaneous causalities between lottery gambling and unemployment in Thailand. The Granger causality and directed acyclic graph (DAG) tests employ time-series data on gambling- and unemployment-related Google Trends indexes from January 2004 to April 2021 (208 monthly observations). These tests are based on the estimates from a vector autoregressive (VAR) model. Granger causality is a way to investigate causality between two variables in a time series. However, this approach cannot detect the contemporaneous causality among variables that occurred within the same period. The contemporaneous causal structure of gambling and unemployment was identified via the data-determined DAG approach. The use of time-series Google Trends indexes in gambling studies is new. Based on this data set, unemployment is found to contemporaneously cause gambling, whereas gambling Granger causes unemployment. The causalities are circular and last for four months.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.1075-1081
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• 2016

The big data analysis has received much attention from the researchers working in various fields because the big data has a great potential in detecting or predicting future events such as epidemic outbreaks and changes in stock prices. Reflecting the current popularity of big data analysis, many authors have proposed methods tracking influenza epidemics based on internet-based information. The recently proposed 'autoregressive model using Google (ARGO) model' (Yang et al., 2015) is one of those influenza tracking models that harness search queries from Google as well as the reports from the Centers for Disease Control (CDC), and appears to outperform the existing method such as 'Google Flu Trends (GFT)'. Although the ARGO predicts well the outbreaks of influenza, this study demonstrates that a classical seasonal autoregressive integrated moving average (SARIMA) model can outperform the ARGO. The SARIMA model incorporates more accurate seasonality of the past influenza activities and takes less input variables into account. Our findings show that the SARIMA model is a functional tool for monitoring influenza epidemics.

• The Journal of Information Systems
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• v.29 no.1
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• pp.289-301
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• 2020

Purpose This study analyzes whether Internet search of cryptocurrency has a causal relationship to return and volatility of cryptocurrency. Design/methodology/approach Google Trend was used as a measure of the level of Internet search, and the parametric tests of Granger causality in the 1st moment and the 2nd moment were adopted as the analysis method. We used Bitcoin's dollar-based price, which is the No. 1 market value among cryptocurrency. Findings The results showed that the Internet search measured by Google Trends has a causal relationship to cryptocurrency in both average and volatility, while there is a difference in causality and its degree according to the search area and category that Google Trend user should set. Because the Granger causality is based on the improvement of prediction, the analysis results of this study indicate that Internet search can be used as a leading indicator in predicting return and volatility of cryptocurrency.

• Journal of Environmental Impact Assessment
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• v.20 no.3
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• pp.257-267
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• 2011

This paper examines the spatial and temporal variability in the shoreline boundary caused by artificial structures in Songdo Beach of South Korea. Quickbird Images of 2003, 2005, 2007, and 2010 extracted from Google Earth were used to identify changing trends of shoreline boundary. The most significant changes were observed in area where groins were extensively established, inducing the sand beach much narrower than before in almost 75% of the area($15070.72m^2$ in 2003 to $3877.46m^2$ in 2010). The Google Earth made it possible to identify area-wide patterns of shoreline change subject to many different type of artificial structures, which cannot be acquired by traditional field sampling. Groin heights, lengths and profiles can be modified during maintenance operations if the Google Earth monitoring indicates that the initial layout is not operating properly as a physical barrier to control sediment transport. It is anticipated that this research could be used as a valuable reference to confirm the outputs from past field researches for coastal processes to respond to storms in more visual and quantitative manner.

• The Journal of Bigdata
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• v.1 no.1
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• pp.67-75
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• 2016

The study analyzed big data extracted from Google and social media to identify factors related to searches on cyber bullying in Korea and America. Korea's cyber bullying analysis was conducted social big data collected from online news sites, blogs, $caf{\acute{e}}s$, social network services and message for between January 1, 2011 and March 31, 2013. Google search trends for the search words of stress, exercise, drinking, and cyber bullying were obtained for January 1, 2004 and December 22, 2013. The main results of this study were as follows: first, the significant factors stress were cyber bullying that Korea more than America. Secondly, a positive relationship was found between stress and drinking, exercise and cyber bullying both Korea and America. Thirdly, significant differences were found all path both Korea and America. The study shows that both adults and teenagers are influenced in Korea. We need to develop online application that if cyber bullying behavior was predicted can intervene in real time because these actual cyber bullying-related exposure to psychological and behavioral characteristic.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.4
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• pp.53-63
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• 2013

Together with soaring interest on Big Data, now there are vigorous reports that unearth various social values lying underneath those data from a number of application areas. Among those reports many are using such data as Internet search histories from Google site, social relationships from Facebook, and transactional or locational traces collected from various ubiquitous devices. Many of those researches, however, are conducted based on the data sets that are accumulated over the North American and European areas, which means that direct interpretation and application of social values exhibited by those researches to the other areas like Korea can be a disturbing task. This research has started from a validation study against Korean environment of the former paper which says an investment strategy that exploits up and down of Google search volume on a carefully selected set of terms shows high market performance. A huge difference between North American and Korean environment can be eye witnessed via the distinction in profit rates that are exhibited by the corresponding set of search terms. Two sets of search terms actually presented low correlation in their profit rates over two financial markets. Even in an experiment which compares the profit rates with two different investment periods with the same set of search terms showed no such meaningful result that outperforms the market average. With all these results, we cautiously conclude that establishing an investment strategy that exploits Internet search volume over a specified word set needs more conscious approach.

• Journal of Environmental Health Sciences
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• v.44 no.6
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• pp.563-571
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• 2018

Objectives: The purpose of this study was to investigate the environmental pollution caused by exposure to air pollution in Korea. Therefore, it is necessary to investigate environmental and health factors through big data. Methods: Among the environmental diseases, the data centered on "percentage per day in 2015 to 2018". Data of environmental diseases and concentrations of air pollution monitoring network were analyzed. Results: Lung cancer and bronchiolitis obliterans were correlated with 0.027 and 0.0158, respectively, in the contamination concentration of fine dust ($PM_{10}$). Ozone, COPD, allergic rhinitis, and bronchiolitis obliterans were correlated with 0.0022, 0.0028 and 0.0093, respectively. At the concentration of $SO_2$ and the diseases of asthma, atopic dermatitis, lung cancer and bronchiolitis obliterans were 0.0008, 0.0523, 0.0016 and 0.0126, respectively. Conclusions: We surveyed the trends of air pollution according to the characteristics of Seoul area in Korea and evaluated the perception of Korea and the world. As a result, respiratory lung disease is thought to be a major factor in exposure to environmental pollution.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.06a
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• pp.6-8
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• 2010

불투수면의 증가는 물, 대기의 순환 과정 교란뿐만 아니라, 자연 생태계 전반에 심각한 문제를 야기하기 때문에 도심의 자연 환경의 질을 평가 할 수 있는 중요한 척도가 되고 있다. 본 연구는 Google Earth와 수치지도를 이용하여 경북대학교 캠퍼스의 불투수율 변화추세를 정량적으로 비교 평가하는 방안을 제안한다. 경북대 캠퍼스 전체 면적에 대한 2003년과 2009년 각각의 불투수면적은 25%에서 42%로 증가하였고, 투수면적은 약 74%에서 57%로 감소하였다. 이러한 경과는 캠퍼스 개발과정에 있어 필요한 개선점을 지침화 할 수 있고, 캠퍼스 자연환경의 보전과정에서 발생할 수 있는 문제점과 시행착오 등을 사전에 점검할 수 있는 중요한 기초자료를 확보할 수 있을 것이다.

• Electronics and Telecommunications Trends
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• v.33 no.2
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• pp.64-76
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• 2018

This paper addresses the antitrust case of Google's general search service to find evidence and logic used for defining markets, and the proof of dominant power and its abuse in detail. This antitrust case has certain meaning because it is not easy to apply traditional approaches to a general search service, which has two-sided market characteristics. This paper finds some implications through an analysis of the antitrust case shown below. First, for market definition, the overall qualitative analysis can be used to draw conclusions without a quantitative analysis, such as a Small but Significant and Non-transitory Increasing in Price (SSNIP) analysis. Second, the multi-homing behavior seems to be one of the key factors in judging the dominant power in Internet-based services. Lastly, the fact that the value of traffic can differ based on the traffic source needs to be considered to address the competition issue of Internet-based services.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.119-120
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• 2021

본 연구의 목적은 Big Data를 활용하여 우리나라 빈곤, 실업, 질병의 우울증과의 인과관계를 규명하고자 한다. 이를 위해 Google 트랜드의 지난 5년간(2015.12. 27~2020.12.20.)의 빈곤-실업-질병-우울증 등의 주제어 중심의 분석을 시도하였다. 분석결과, 빈곤(B=.295, p<.001)과 실업(B=.404, p<.001)은 질병에 유의미한 영향을 미치며, 빈곤(B=.150, p<.01)과 질병(B=.186, p<.01) 및 실업(B=.466, p<.001)은 우울증에 유의미한 영향을 미치는 것으로 나타났다.