• Title/Summary/Keyword: Big-data Analysis

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A Study on Popular Sentiment for Generation MZ: Through social media (SNS) sentiment analysis (MZ세대에 대한 대중감성 연구: 소셜미디어(SNS) 감성 분석을 통해)

  • Myung-suk Ann
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.1
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    • pp.19-26
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    • 2023
  • In this study, the public sensitivity of the 'MZ generation' was examined through the social media big data sensitivity analysis method. For the analysis, the consumer account SNS text was examined, and positive and negative emotional factors were presented by classifying external sensibilities and emotions of the MZ generation. In conclusion, the positive emotions of liking and interest in relation to the "MZ generation" were 72.1%, higher than the negative emotional ratio of 27.9%. In positive sensitivity, the older generation showed 'a favorable feeling for the individuality and dignifiedness of the MZ generation' and 'interest in the MZ generation with new values'. In contrast, the MZ generation has a favorable feeling for 'the fact that they are a generation of their own boldness, youthfulness and individuality' and 'small growthism'. Negative sensitivity outside the MZ generation was found to be 'A concern about the marriage avoidance, employment difficulties, debt investment, and resignation trends of the MZ generation', 'Hate the MZ generation who treats Kkondae' and 'Difficult to talk to the MZ generation'. On the other hand, the negative emotions felt by the MZ generation itself were 'Rejection of generalization', 'Rejection of generation and gender conflicts', 'Rejection of competition worse than the older generation', 'Relative failure of the rich era', and 'Sadness to live in a predicted climate disaster'. Therefore, the older generation should not look at the MZ generation in general, but as individuals, and should alleviate conflicts with intergenerational understanding and empathy. there is a need for community consideration to solve generational conflicts, gender conflicts, and environmental problems.

Evaluation of Extreme Rainfall based on Typhoon using Nonparametric Monte Carlo Simulation and Locally Weighted Polynomial Regression (비매개변수적 모의발생기법과 지역가중다항식을 이용한 태풍의 극치강우량 평가)

  • Oh, Tae-Suk;Moon, Young-Il;Chun, Si-Young;Kwon, Hyun-Han
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.2B
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    • pp.193-205
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    • 2009
  • Typhoons occurred in the tropical Pacific region, these might be affected the Korea moving toward north. The strong winds and the heavy rains by the typhoons caused a natural disaster in Korea. In the research, the heavy rainfall events based on typhoons were evaluated quantitative through various statistical techniques. First, probability precipitation and typhoon probability precipitation were compared using frequency analysis. Second, EST probability precipitation was calculated by Empirical Simulation Techniques (EST). Third, NL probability precipitation was estimated by coupled Nonparametric monte carlo simulation and Locally weighted polynomial regression. At the analysis results, the typhoons can be effected Gangneung and Mokpo stations more than other stations. Conversely, the typhoons can be effected Seoul and Inchen stations less than other stations. Also, EST and NL probability precipitation were estimated by the long-term simulation using observed data. Consequently, major hydrologic structures and regions where received the big typhoons impact should be review necessary. Also, EST and NL techniques can be used for climate change by the global warming. Because, these techniques used the relationship between the heavy rainfall events and the typhoons characteristics.

Smoking-attributable Mortality in Korea, 2020: A Meta-analysis of 4 Databases

  • Eunsil Cheon;Yeun Soo Yang;Suyoung Jo;Jieun Hwang;Keum Ji Jung;Sunmi Lee;Seong Yong Park;Kyoungin Na;Soyeon Kim;Sun Ha Jee;Sung-il Cho
    • Journal of Preventive Medicine and Public Health
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    • v.57 no.4
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    • pp.327-338
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    • 2024
  • Objectives: Estimating the number of deaths caused by smoking is crucial for developing and evaluating tobacco control and smoking cessation policies. This study aimed to determine smoking-attributable mortality (SAM) in Korea in 2020. Methods: Four large-scale cohorts from Korea were analyzed. A Cox proportional-hazards model was used to determine the hazard ratios (HRs) of smoking-related death. By conducting a meta-analysis of these HRs, the pooled HRs of smoking-related death for 41 diseases were estimated. Population-attributable fractions (PAFs) were calculated based on the smoking prevalence for 1995 in conjunction with the pooled HRs. Subsequently, SAM was derived using the PAF and the number of deaths recorded for each disease in 2020. Results: The pooled HR for all-cause mortality attributable to smoking was 1.73 for current men smokers (95% confidence interval [CI], 1.53 to 1.95) and 1.63 for current women smokers (95% CI, 1.37 to 1.94). Smoking accounted for 33.2% of all-cause deaths in men and 4.6% in women. Additionally, it was a factor in 71.8% of men lung cancer deaths and 11.9% of women lung cancer deaths. In 2020, smoking was responsible for 53 930 men deaths and 6283 women deaths, totaling 60 213 deaths. Conclusions: Cigarette smoking was responsible for a significant number of deaths in Korea in 2020. Monitoring the impact and societal burden of smoking is essential for effective tobacco control and harm prevention policies.

Predicting the Direction of the Stock Index by Using a Domain-Specific Sentiment Dictionary (주가지수 방향성 예측을 위한 주제지향 감성사전 구축 방안)

  • Yu, Eunji;Kim, Yoosin;Kim, Namgyu;Jeong, Seung Ryul
    • Journal of Intelligence and Information Systems
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    • v.19 no.1
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    • pp.95-110
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    • 2013
  • Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

Calibration of Gauge Rainfall Considering Wind Effect (바람의 영향을 고려한 지상강우의 보정방법 연구)

  • Shin, Hyunseok;Noh, Huiseong;Kim, Yonsoo;Ly, Sidoeun;Kim, Duckhwan;Kim, Hungsoo
    • Journal of Wetlands Research
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    • v.16 no.1
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    • pp.19-32
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    • 2014
  • The purpose of this paper is to obtain reliable rainfall data for runoff simulation and other hydrological analysis by the calibration of gauge rainfall. The calibrated gauge rainfall could be close to the actual value with rainfall on the ground. In order to analyze the wind effect of ground rain gauge, we selected the rain gauge sites with and without a windshield and standard rain gauge data from Chupungryeong weather station installed by standard of WMO. Simple linear regression model and artificial neural networks were used for the calibration of rainfalls, and we verified the reliability of the calibrated rainfalls through the runoff analysis using $Vflo^{TM}$. Rainfall calibrated by linear regression is higher amount of rainfall in 5%~18% than actual rainfall, and the wind remarkably affects the rainfall amount in the range of wind speed of 1.6~3.3m/s. It is hard to apply the linear regression model over 5.5m/s wind speed, because there is an insufficient wind speed data over 5.5m/s and there are also some outliers. On the other hand, rainfall calibrated by neural networks is estimated lower rainfall amount in 10~20% than actual rainfall. The results of the statistical evaluations are that neural networks model is more suitable for relatively big standard deviation and average rainfall. However, the linear regression model shows more suitable for extreme values. For getting more reliable rainfall data, we may need to select the suitable model for rainfall calibration. We expect the reliable hydrologic analysis could be performed by applying the calibration method suggested in this research.

The Effect of Patent Citation Relationship on Business Performance : A Social Network Analysis Perspective (특허 인용 관계가 기업 성과에 미치는 영향 : 소셜네트워크분석 관점)

  • Park, Jun Hyung;Kwahk, Kee-Young
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.127-139
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    • 2013
  • With an advent of recent knowledge-based society, the interest in intellectual property has increased. Firms have tired to result in productive outcomes through continuous innovative activity. Especially, ICT firms which lead high-tech industry have tried to manage intellectual property more systematically. Firm's interest in the patent has increased in order to manage the innovative activity and Knowledge property. The patent involves not only simple information but also important values as information of technology, management and right. Moreover, as the patent has the detailed contents regarding technology development activity, it is regarded as valuable data. The patent which reflects technology spread and research outcomes and business performances are closely interrelated as the patent is considered as a significant the level of firm's innovation. As the patent information which represents companies' intellectual capital is accumulated continuously, it has become possible to do quantitative analysis. The advantages of patent in the related industry information and it's standardize information can be easily obtained. Through the patent, the flow of knowledge can be determined. The patent information can analyze in various levels from patent to nation. The patent information is used to analyze technical status and the effects on performance. The patent which has a high frequency of citation refers to having high technological values. Analyzing the patent information contains both citation index analysis using the number of citation and network analysis using citation relationship. Network analysis can provide the information on the flows of knowledge and technological changes, and it can show future research direction. Studies using the patent citation analysis vary academically and practically. For the citation index research, studies to analyze influential big patent has been conducted, and for the network analysis research, studies to find out the flows of technology in a certain industry has been conducted. Social network analysis is applied not only in the sociology, but also in a field of management consulting and company's knowledge management. Research of how the company's network position has an impact on business performances has been conducted from various aspects in a field of network analysis. Social network analysis can be based on the visual forms. Network indicators are available through the quantitative analysis. Social network analysis is used when analyzing outcomes in terms of the position of network. Social network analysis focuses largely on centrality and structural holes. Centrality indicates that actors having central positions among other actors have an advantage to exert stronger influence for exchange relationship. Degree centrality, betweenness centrality and closeness centrality are used for centrality analysis. Structural holes refer to an empty place in social structure and are defined as efficiency and constraints. This study stresses and analyzes firms' network in terms of the patent and how network characteristics have an influence on business performances. For the purpose of doing this, seventy-four ICT companies listed in S&P500 are chosen for the sample. UCINET6 is used to analyze the network structural characteristics such as outdegree centrality, betweenness centrality and efficiency. Then, regression analysis test is conducted to find out how these network characteristics are related to business performance. It is found that each network index has significant impacts on net income, i.e. business performance. However, it is found that efficiency is negatively associated with business performance. As the efficiency increases, net income decreases and it has a negative impact on business performances. Furthermore, it is shown that betweenness centrality solely has statistically significance for the multiple regression analysis with three network indexes. The patent citation network analysis shows the flows of knowledge between firms, and it can be expected to contribute to company's management strategies by analyzing company's network structural positions.

A Study on the Road Safety Analysis Model: Focused on National Highway Areas in Cheonbuk Province (도로 안전성 분석 모형에 관한 연구: 전라북도 국도 권역을 중심으로)

  • Lim, Joonbeom;Kim, Joon-Ki;Lee, Soobeom;Kim, Hyunjin
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.2
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    • pp.583-595
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    • 2014
  • Currently, Korean transportation policies are aiming for increase of safety and environment-friendly and efficient operation, by avoiding construction and expansion of roads, and upgrading road alignments and facilities. This is revealed by that there have been 22 road expansion projects (30%) and 50 road improvement projects (70%) under the 3rd Five-Year Plan for National Highways ('11~'15), while there were 53 road expansion projects (71%) and 22 road improvement projects (29%) under the 2nd Five-Year Plan for National Highways. For more effective road improvement projects, there is a need of choosing projects after an objective and scientific safety assessment of each road, and assessing safety improvement depending on projects. This study is intended to develop a model for this road safety analysis and assessment. The major objective of this study is creating a road safety analysis and assessment model appropriate for Korean society, based on the HSM (Highway Safety Manual) of the U.S. In order to build up data for model development, the sections thought to have identical geometrical structure factors in 5 lines, Cheonbuk province, were divided as homogeneous sections, and representative values of geometric structures, facilities, traffic volume, climate conditions and land usage were collected from the 1,452 sections divided. In order to build up data for model development, the sections thought to have identical geometrical structure factors in 5 lines, Cheonbuk province, were divided as homogeneous sections, and representative values of geometric structures, facilities, traffic volume, climate conditions and land usage were collected from the 1,452 sections divided. The collected data was processed correlation analysis of each road element was implemented to see which factor had a big effect on traffic accidents. On the basis of these results, then, an accident model was established as a negative binomial regression model.Using the developed model, an Crash Modification Factor (CMF) which determines accident frequency changes depending on safety performance function (SPF) predicting the number of accident occurrence through traffic volume and road section expansion, road geometric structure and traffic properties, was extracted.

Promoting College Graduate Students Motivating Entering on Small and Medium Sized Company : Based on the Expectation Value Theory (대학졸업생들의 중소기업 취업촉진 방안에 관한 연구 : 기대가치이론을 중심으로)

  • Ha, Kyu Soo
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.9 no.4
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    • pp.55-64
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    • 2014
  • While small and medium-sized companies are suffering from a shortage of workers as a result of social tendency to avoid those companies, college graduates still prefer large companies or governmental positions, which consequently results in inconsistencies in the demand and supply of work forces. The gap between them is getting so bad that employment difficulties are exacerbating. Accordingly this study tries to search for potential employee's expected value factors which make people select small and medium companies not big companies. A survey was conducted from October 1 to october 30, 2012 with university students in the Seoul metropolitan area. a total of 350 questionnaires were distributed and 335 were collected. of these, 332 questionnaires were used for data analyses excluding questionnaires with missing values. Data was analyzed by frequency, descriptive factor, reliability, and regression with SPSS win 18.0 program The result of this study were as follows. A factor analysis extracted four factors comprising small and medium companies, which we named career(factor 1), working environment(factor 2), working achievement(factor 3), job security (factor 4). This study showed that small and medium companies' preference were affected by the career, working environment, job security, corporate reputation, salary.

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Effects of Residential Environment on Life Satisfaction Among the Middle-aged: Focused on the Moderating Effects of Social Capital (중장년층의 주거환경이 삶의 만족도에 미치는 영향: 사회적 자본의 조절효과를 중심으로)

  • Lim, Sun Mi;Lee, Bo Young
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.11 no.1
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    • pp.49-63
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    • 2016
  • In the 21st century when people're pursuing the qualitative improvement of life, the concern about the quality of housing is growing as living standards have been improved and the desire for life has been various. Life satisfaction can be found that basic needs of residential satisfaction have been met in life, and the quality of life will be higher with the fulfillment of these desires. Humans all live in social relations, which have a big impact on the quality of life of individuals in a variety of aspects. Thus, this researcher tried to investigate middle-aged people's residential environment and the actual situation of social capital and to examine the effect of social capital on the relationship between residential environment satisfaction and life satisfaction through an empirical study. The survey was conducted for middle-aged people to collect data, 500 copies of a questionnaire were distributed and 490 of them were collected, and then the actual analysis of 484 copies without missing values was done using SPSS Ver. 21.0. As a result, first, middle-aged people's residential environment had a significant effect on life satisfaction. Second, moderating effects of social capital between middle-aged people's residential environment satisfaction and life satisfaction showed a partly significant influence. Depending on these results, the researcher try to offer the direction for the improvement of the quality of life to middle-aged people and useful data to establish Korea housing policy.

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Analysis of Domestic Water Pollution Accident and Response Management (국내 수질오염사고 현황 분석과 대응 체계)

  • Lee, Jae-Kyun;Kim, Tae-O;Jung, Yong-Jun
    • Journal of Wetlands Research
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    • v.15 no.4
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    • pp.529-534
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    • 2013
  • Domestic water pollution accidents and response management were analysed on the basis of collected data from the latest 5 years. Although average 66.7 number of accidents were happened every year, no damages of human life were reported yet. According to the data collected, the accidents were occurred at Han river, Nakdong river, Keum river, Youngsang river and other rivers, where the percentages were 25.4%, 20.3%, 12%, 8% and 29.7%, respectively. Main reasons were blamed for negligent management, mixed influences, natural phenomenon and traffic accident. Response activities were performed in the case of the oil leak, the fish death caused by water environment, the spill of chemicals. From the diagnosis of water pollution accidents, it is recommended that the legistration of all control centers for their roles and duties was made in case of the big accidents as well as the small/middle accidents.