• Title/Summary/Keyword: Data trend analysis

Search Result 3,056, Processing Time 0.027 seconds

Analyzing Global Startup Trends Using Google Trends Keyword Big Data Analysis: 2017~2022 (Google Trends 의 키워드 빅데이터 분석을 활용한 글로벌 스타트업 트렌드 분석: 2017~2022 )

  • Jaeeog Kim;Byunghoon Jeon
    • Journal of Platform Technology
    • /
    • v.11 no.4
    • /
    • pp.19-34
    • /
    • 2023
  • In order to identify the trends and insights of 'startups' in the global era, we conducted an in-depth trend analysis of the global startup ecosystem using Google Trends, a big data analysis platform. For the validity of the analysis, we verified the correlation between the keywords 'startup' and 'global' through BIGKinds. We also conducted a network analysis based on the data extracted using Google Trends to determine the frequency of searches for the keyword or term 'startup'. The results showed a strong positive linear relationship between the keywords, indicating a statistically significant correlation (correlation coefficient: +0.8906). When exploring global startup trends using Google Trends, we found a terribly similar linear pattern of increasing and decreasing interest in each country over time, as shown in Figure 4. In particular, startup interest was low in the range of 35 to 76 from mid-2020 due to the COVID-19 pandemic, but there was a noticeable upward trend in startup interest after March 2022. In addition, we found that the interest in startups in each country except South Korea is very similar, and the related topics are startup company, technology, investment, funding, and keyword search terms such as best startup, tech, business, invest, health, and fintech are highly correlated.

  • PDF

Dynamic Simple Correspondence Analysis

  • Choi Yong-Seok;Hyun Gee Hong;Seo Myung Rok
    • Communications for Statistical Applications and Methods
    • /
    • v.12 no.1
    • /
    • pp.199-205
    • /
    • 2005
  • In general, simple correspondence analysis has handled mainly correspondence relations between the row and column categories but can not display the trends of their change over the time. For solving this problem, we will propose DSCA(Dynamic Simple Correspondence Analysis) of transition matrix data using supplementary categories in this study, Moreover, DSCA provides its trend of the change for the future by predicting and displaying trend toward the change from a standard point of time to the next.

Development of Reliability Analysis Procedures for Repairable Systems with Interval Failure Time Data and a Related Case Study (구간 고장 데이터가 주어진 수리가능 시스템의 신뢰도 분석절차 개발 및 사례연구)

  • Cho, Cha-Hyun;Yum, Bong-Jin
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.14 no.5
    • /
    • pp.859-870
    • /
    • 2011
  • The purpose of this paper is to develop reliability analysis procedures for repairable systems with interval failure time data and apply the procedures for assessing the storage reliability of a subsystem of a certain type of guided missile. In the procedures, the interval failure time data are converted to pseudo failure times using the uniform random generation method, mid-point method or equispaced intervals method. Then, such analytic trend tests as Laplace, Lewis-Robinson, Pair-wise Comparison Nonparametric tests are used to determine whether the failure process follows a renewal or non-renewal process. Monte Carlo simulation experiments are conducted to compare the three conversion methods in terms of the statistical performance for each trend test when the underlying process is homogeneous Poisson, renewal, or non-homogeneous Poisson. The simulation results show that the uniform random generation method is best among the three. These results are applied to actual field data collected for a subsystem of a certain type of guided missile to identify its failure process and to estimate its mean time to failure and annual mean repair cost.

A Trend Analysis on E-sports using Social Big Data

  • Kyoung Ah YEO;Min Soo KIM
    • Journal of Sport and Applied Science
    • /
    • v.8 no.1
    • /
    • pp.11-17
    • /
    • 2024
  • Purpose: The purpose of the study was to understand a trend of esports in terms of gamers' and fans' perceptions toward esports using social big data. Research design, data, and methodology: In this study, researchers first selected keywords related to esports. Then a total of 10,138 buzz data created at twitter, Facebook, news media, blogs, café and community between November 10, 2022 and November 19, 2023 were collected and analyzed with 'Textom', a big data solution. Results: The results of this study were as follows. Firstly, the news data's main articles were about competitions hosted by local governments and policies to revitalize the gaming industry. Secondly, As a result of esports analysis using Textom, there was a lot of interest in the adoption of the Hangzhou Asian Games as an official event and various esports competitions. As a result of the sentiment analysis, the positive content was related to the development potential of the esports industry, and the negative content was a discussion about the fundamental problem of whether esports is truly a sport. Thirdly, As a result of analyzing social big data on esports and the Olympics, there was hope that it would be adopted as an official event in the Olympics due to its adoption as an official event in the Hangzhou Asian Games. Conclusions: There was a positive opinion that the adoption of esports as an official Olympic event had positive content that could improve the quality of the game, and a negative opinion that games with actions that violate the Olympic spirit, such as murder and assault, should not be adopted as an official Olympic event. Further implications were discussed.

A Study of Discriminant Analysis about Korean Quick Response System Adoption (국내(國內) 신속대응(迅速對應)시스템 도입업체(導入業體)의 판별분석(判別分析) 연구(硏究))

  • Ko, Eun-Ju
    • Journal of Fashion Business
    • /
    • v.4 no.3
    • /
    • pp.103-114
    • /
    • 2000
  • The purpose of this study was to test the discriminant analysis model of Quick Response system and to examine the detailed relationship between each discriminant factor and Quick Response adoption. In this discriminant analysis model of Quick Response system, firm size, strategic type, product category, fashion trend, selling time and the Quick Response benefits were included as discriminant factors. Onehundred and two subjects were randomly selected for the survey study and discriminant analysis, descriptive analysis, t-test, and x square test were used for the data analysis. The results of this study were: 1. Wilks Lambda and F value support the discriminant analysis model that, taken together firm size, strategic type, product category, fashion trend, selling time and the Quick Response benefits significantly help to explain Quick Response adoption. 2. The importance of discriminant ability was, in order, firm size, the Quick Response benefits, women's wear, fashion trend, analyzer, selling time, reactor, defender and men's wear. 3. The discriminant function had the high hit ratio, so this can be well used for the classification of Quick Response adoption/nonadoption.

  • PDF

Intervention Analysis of Urbanization Effect on Rainfall Data at the Seoul Rain Gauge Station (서울지점 강우자료에 나타난 도시화의 간섭 분석)

  • Yoo, Chul-Sang;Kim, Dae-Ha;Park, Sang-Hyoung;Kim, Byung-Su;Park, Chang-Yeol
    • Journal of Korea Water Resources Association
    • /
    • v.40 no.8
    • /
    • pp.629-641
    • /
    • 2007
  • This study estimated the urbanization effect of Seoul, the largest city in Korea, on its rainfall. For a comparative analysis, two different data sets are used: One is the precipitation data at the Jeonju rain gauge station, which has a relatively long record length but least urbanization effect, and the other at the Ichon rain gauge station, which has a short record length but located very near to Seoul with least urbanization effect. Also, the difference of the rainfall between Seoul and Jeonju rain gauge stations, as an indicator of urbanization effect, is quantified by use of the intervention model. As a result, it was found that the maximum rainfall intensity of the annual maximum rainfall events shows the increasing trend, its duration the decreasing trend, and the mean intensity the decreasing trend especially after 1960. Also, the quantification of urbanization effect using the intervention model shows that the increasing trend of rainfall intensity and total volume is still on going.

Temporal Analysis of Trends in Dissolved Organic Matter in Han River Water

  • Lee, Hye-Won;Choi, Jung-Hyun
    • Environmental Engineering Research
    • /
    • v.14 no.4
    • /
    • pp.256-260
    • /
    • 2009
  • This study used the extensive monitoring datasets of the Korea Ministry of Environment to examine trends in dissolved organic carbon (DOC) in Han River raw water. To estimate the organic contents of water, we adopted allied parameters such as biochemical oxygen demand (BOD) and chemical oxygen demand (COD) as substitutes for DOC. Spatial and temporal analyses were performed on monthly BOD and COD data from 36 monitoring stations (14 for Main Han River, 7 for North Han River and 15 for South Han River) measured from 1989 to 2007. The results of trend analysis indicated that, on the whole, water quality according to BOD showed a downward trend at more than 67% of monitoring stations (9 for Main Han River, 6 for North Han River and 9 for South Han River). However, the water quality of COD showed an upward trend at more than 78% of monitoring stations (8 for Main Han River, 7 for North Han River and 13 for South Han River). The upward trend of COD contrary to the BOD trend indicates that there has been an increase in recalcitrant organic matter in Han River water that is not detectable by means of BOD.

Trend Analysis on Clothing Care System of Consumer from Big Data (빅데이터를 통한 소비자의 의복관리방식 트렌드 분석)

  • Koo, Young Seok
    • Fashion & Textile Research Journal
    • /
    • v.22 no.5
    • /
    • pp.639-649
    • /
    • 2020
  • This study investigates consumer opinions of clothing care and provides fundamental data to decision-making for oncoming development of clothing care system. Textom, a web-matrix program, was used to analyze big data collected from Naver and Daum with a keyword of "clothing care" from March 2019 to February 2020. A total of 22, 187 texts were shown from the big data collection. Collected big data were analyzed using text-mining, network, and CONCOR analysis. The results of this study were as follows. First, many keywords related to clothing care were shown from the result of frequency analysis such as style, Dryer, LG Electronics, Product, Customer, Clothing, and Styler. Consumers were well recognizing and having an interest in recent information related to the clothing care system. Second, various keywords such as product, function, brand, and performance, were linked to each other which were fundamentally related to the clothing care. The interest in products of the clothing care system were linked to product brands that were also naturally linked to consumer interest. Third, the keywords in the network showed similar attributes from the result of CONCOR analysis that were classified into 4 groups such as the characteristics of purchase, product, performance, and interest. Lastly, positive emotions including goodwill, interest, and joy on the clothing care system were strongly expressed from the result of the sentimental analysis.

Trend Analysis of Research Using Evaluation Tools of Languages Abilities for Young Children: Based on Early Children Education Journals registered with the Korea Research Foundation (유아 언어능력 평가연구의 동향 분석 -한국학술진흥재단 등재 학회지를 중심으로)

  • Youn, Jin-Ju
    • Korean Journal of Human Ecology
    • /
    • v.16 no.4
    • /
    • pp.677-690
    • /
    • 2007
  • This study has a goal to read a trend of language research by analysing evaluation tools and methods that researchers have used for assessing young children's language abilities. Thus the study has chosen 237 language ability evaluation methods out of 121 young child's language ability evaluation researches. The treatises were selected from 4 types of early childhood education journals registered on the Korea Research Foundation. The data analysis was employed for processing the frequency and percentage of the collected data. The results were as follows: First, of single age groups the subject group most selected was five-year-olders and of mixed-age groups the subject group most selected was from three to five, and the number of subjects in researches were mostly below fifty children. The researches were sorted into an 'experimental/ investigational researching' type that has been frequently re-utilized by others, an 'interview type' using a data collection method, and a 'difference verification' type using a data analysis method which has been used in majority of studies. Second, the number of treaties that required data analysis has increased since 1996. Concludingly, the analysis of young child's language ability evaluation tools shows that the purposes of many researches were concentrated on studying children's knowledge about language, children's language functions such as speaking, reading, writing and listening, while evaluation contents were focused on speaking and writing.

Characteristic Change Analysis of Rainfall Events using Daily Rainfall Data (일강우자료를 이용한 강우사상의 변동 특성 분석)

  • Oh, Tae-Suk;Moon, Young-Il
    • Journal of Korea Water Resources Association
    • /
    • v.42 no.11
    • /
    • pp.933-951
    • /
    • 2009
  • Climate change of global warming may affect the water circulation in Korea. Rainfall is occurred with complex of multiple climatic indices. Therefore, the rainfall is one of the most significant index due to climate change in the process of water circulation. In this research, multiple time series data of rainfall events were extracted to represent the rainfall characteristics. In addition, the occurrence of rainfall time series analyzed by annual, seasonal and monthly data. Analysis method used change analysis of mean and standard deviation and trend analysis. Also, changes in rainfall characteristics and the relative error was calculated during the last 10 years for comparison with past data. At the results, significant statistical results weren't showed by randomness of rainfall data. However, amount of rainfall generally increased last 10 years, and number of raining days had trend of decrease. In addition, seasonal and monthly changes in the rainfall characteristics can be found to appear differently.