• 한국경영과학회지
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• 제38권4호
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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.

• 산업경영시스템학회지
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• 제43권2호
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• pp.126-136
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• 2020

Recently, unmanned aerial vehicles (UAV, Drone) are highly regarded for their potential in the agricultural field, and research and development are actively conducted for various purposes. Therefore, in this study, to present a framework for tracking research trends in UAV use in the agricultural field, we secured a keyword search strategy and analyzed social network, a methodology used to analyze recent research trends or technological trends as an analysis model applied. This study consists of three stages. As a first step in data acquisition, search terms and search formulas were developed for experts in accordance with the Keyword Search Strategy. Data collection was conducted based on completed search terms and search expressions. As a second step, frequency analysis was conducted by country, academic field, and journal based on the number of thesis presentations. Finally, social network analysis was performed. The analysis used the open source programming language 'Python'. Thanks to the efficiency and convenience of unmanned aerial vehicles, this field is growing rapidly and China and the United States are leading global research. Korea ranked 18th, and bold investment in this field is needed to advance agriculture. The results of this study's analysis could be used as important information in government policy making.

• 한국문헌정보학회지
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• 제45권1호
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• pp.377-393
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• 2011

이 연구에서는 국내 주요 검색 포털인 네이버 이용자들의 검색 행태 추이를 조사, 분석하였다. 즉 1년 동안 분기별로 네이버에 입력된 질의들을 대상으로 질의의 입력 행태, 오타 입력 행태, 멀티미디어 검색 행태, 결과 문서 클릭 행태 등의 추이를 조사하였다. 이를 위하여 이용자들이 입력한 통합 검색 질의들로 구성된 질의 로그와 질의에 대한 검색 결과에서 이용자들이 조회한 문서를 기록한 클릭 로그를 분석하였다. 연구결과, 입력된 질의의 길이 및 주제, 멀티미디어 질의의 특징 및 비율, 오타의 비율 등에 있어서는 1년 동안 큰 변화 없이 일정한 것으로 나타났다. 반면, 질의별로 발생되는 클릭 횟수는 시간이 지남에 따라 점진적으로 증가하는 것으로 나타났다. 본 연구의 결과는 향후 포털의 효과적인 콘텐츠 구축 및 검색 알고리즘 개발에 활용될 수 있을 것으로 기대된다.

• 대한본초학회지
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• 제31권4호
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• pp.93-100
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• 2016

Objectives : The internet is the most common method to investigate information. It is showed that 75.2% of Internet users of 20s had health information search experience. So this study is aim to understanding of interest of public about the herbal medicine using internet search query volume data.Methods : The Naver that is the top internet portal web service of the Republic of Korea has provided an Internet search query volume data from January 2007 to the current through the Naver data lab (http://datalab.naver.com) service. We have collected search query volume data which was provided by the Naver in 606 herbal medicine names and sorted the data by peak and total search volume.Results : The most frequently searched herbal medicines which has less bias and sorted by peak search volume is 'wasong (와송)'. And the most frequently searched herbal medicines which has less bias and sorted by total search volume is 'hasuo (하수오)'.Conclustions : This study is showed that the rank of interest of public about herbal medicines. Among the above herbal medicines, some herbal medicines had supply issue. And there are some other herbal medicines that had very little demand in Korean medicine market, but highly interested public. So it is necessary to monitor for these herbal medicines which is highly interested of the public. Furthermore if the reliability of the data obtained on the basis of these studies, it is possible to be utilizing herbal medicine monitoring service.

• 동의신경정신과학회지
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• 제34권1호
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• pp.13-21
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• 2023

Objectives: The aim of this study was to analyze correlations among searches of hwa-byung, depression, and suicide using big data. Methods: Keywords searches were performed using both Google Trends and Naver Data Lab on December 13, 2022. From 2016 to 2022, search results for keywords 'hwa-byung', 'depression', and 'suicide' were extracted with a score between 0 and 100 in terms of relative search popularity (RSP). Monthly time analysis, correlation analysis, and regional analysis were then conducted for these scores. Results: Regardless of the search period, RSP for both portal sites was in the order of 'suicide', 'depression', and 'hwa-byung'. Over time, search for 'depression' tended to increase in Google (slope: 0.0092), whereas search for 'hwa-byung' showed a slight increase in Naver (slope: 0.0024). Correlation coefficient for search terms 'depression' and 'suicide' was 0.3969 in Google Trends and 0.4459 in Naver Data Lab, showing clear positive correlations. On the other hand, there was little correlation between search results of 'hwa-byung' and 'depression' or between 'hwa-byung' and 'suicide'. However, compared to males, females showed higher positive associations between search results of 'hwa-byung' and 'depression' and between 'hwa-byung' and 'suicide'. Search terms 'depression' and 'suicide' showed high RSPs in most regions in South Korea. However, 'hwa-byung' had distinct regional differences in terms of RSP. Conclusions: Results of this study will help us understand Korean public's perception of the relevance of hwa-byung, depression, and suicide and plan future research in this topic. In addition, findings of this study may provide future public health implications for reducing the high suicide rate in Korea.

• 산업경영시스템학회지
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• 제43권2호
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• pp.14-24
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• 2020

Google Trends is a useful tool not only for setting search periods, but also for providing search volume to specific countries, regions, and cities. Extant research showed that the big data from Google Trends could be used for an on-line market analysis of opinion sensitive products instead of an on-site survey. This study investigated the market share of tumor necrosis factor-alpha (TNF-α) inhibitor, which is in a great demand pharmaceutical product, based on big data analysis provided by Google Trends. In this case study, the consumer interest data from Google Trends were compared to the actual product sales of Top 3 TNF-α inhibitors (Enbrel, Remicade, and Humira). A correlation analysis and relative gap were analyzed by statistical analysis between sales-based market share and interest-based market share. Besides, in the country-specific analysis, three major countries (USA, Germany, and France) were selected for market share analysis for Top 3 TNF-α inhibitors. As a result, significant correlation and similarity were identified by data analysis. In the case of Remicade's biosimilars, the consumer interest in two biosimilar products (Inflectra and Renflexis) increased after the FDA approval. The analytical data showed that Google Trends is a powerful tool for market share estimation for biosimilars. This study is the first investigation in market share analysis for pharmaceutical products using Google Trends big data, and it shows that global and regional market share analysis and estimation are applicable for the interest-sensitive products.

• 정보처리학회논문지D
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• 제15D권4호
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• pp.485-494
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• 2008

인터넷이 광범위하게 활용됨에 따라 검색 키워드, 멀티미디어 객체, 웹 페이지, 블로그 등의 다양한 웹 객체들이 크게 증가하고 있다. 이러한 웹 객체들의 인기도는 시간에 따라 변화하며, 그러한 웹 객체 인기도의 시간적 패턴에 대한 마이닝이 여러 가지 웹 응용에 필요한 중요한 연구 과제가 되고 있다. 예를 들어, 검색 키워드에 대한 인기도 패턴의 분석은 앞으로 인기가 높아질 키워드를 미리 예측할 수 있게 하여 광고주들에게 키워드를 판매하기 위한 가격을 결정하는 데에 중요한 자료가 될 수 있다. 하지만, 웹 객체 인기도가 시간에 따라 변화하고 웹 객체의 개수가 매우 방대하다는 특성으로 인하여 웹 객체 인기도에 대한 분석은 매우 어려운 문제이다. 본 논문에서는 웹 객체 인기도의 시간적 패턴을 마이닝하기 위한 효율적인 알고리즘을 제안한다. 본 논문은 웹 객체 인기도를 시계열로 표현하고, 두 웹 객체 인기도 간의 유사성을 측정하기 위하여 gap 척도를 제안한다. gap 척도의 효율적인 계산을 위하여 FFT를 활용한 알고리즘을 제안하고, 밀도기반 클러스터링 알고리즘을 이용하여 유사한 인기도 추세를 갖는 웹 객체들의 클러스터를 생성한다. 본 논문에서는 웹 객체 인기도가 특정 분포를 따르거나 주기적이라고 가정하지 않는다. Google Trends 웹 사이트로부터 구한 검색 키워드 인기도를 이용한 실험을 통하여, 제안된 알고리즘이 실세계 응용에서 유용함을 보인다.

• 한국문헌정보학회지
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• 제39권2호
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• pp.147-160
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• 2005

본 연구에서는 1년이라는 장기간에 걸쳐 네이버에 입력된 검색 질의들의 표본과 각 질의에 대한 클릭 로그에 근거하여 국내 웹 이용자의 검색 행태 추이를 분석하였다. 질의의 형태에 대한 조사 결과, 계절별, 주중과 주말 요일별 질의 형태의 분포에 있어서 유의한 차이가 있는 것으로 나타났다. 또한 웹 이용자들이 입력한 질의의 주제 역시 계절별, 주중과 주말, 요일별로 변화하는 것으로 나타났다. 반면 1년 동안을 전체적으로 살펴볼 때 사이트 검색과 내용 검색의 비율 그리고 주제의 비율이 큰 변화 없이 일정한 상태를 유지하였다. 본 연구의 결과는 인터넷 검색 포탈 업체들의 효과적인 컨텐츠 구축 및 효율적인 검색 시스템 개발에 기여할 것으로 기대된다.

• Journal of Electrical Engineering and Technology
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• 제11권1호
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• pp.227-233
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• 2016

Google Trends provides weekly information on keyword search frequency on the Google search engine. Search volume patterns for the search keyword can also be analyzed based on category and by the location of those making the search. Also, Google provides “Hot searches” and “Top charts” including top and rising searches that include the search keyword. All this information is kept up to date, and allows trend comparisons by providing past weekly figures. In this study, we present a predictive model for TV markets using the searched data in Google search engine (Google Trend data). Using a predictive model for the market and analysis of the Google Trend data, we obtained an efficient and meaningful result for the TV market, and also determined highly ranked countries and cities. This method can provide very useful information for TV manufacturers and others.

• 한국정보시스템학회지:정보시스템연구
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• 제29권1호
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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.