• Title/Summary/Keyword: data mining

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Wireless Earphone Consumers Using LDA Topic Modeling Comparative Analysis of Purchase Intention and Satisfaction: Focused on Samsung and Apple wireless earphone reviews in Coupang (LDA 토픽 모델링을 활용한 무선이어폰 소비자 구매 의도 및 만족도 비교 분석: 쿠팡에서의 삼성과 애플 무선이어폰 리뷰를 중심으로)

  • Tuul Yondon;Tae-Gu Kang
    • Journal of Industrial Convergence
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    • v.21 no.8
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    • pp.23-33
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    • 2023
  • Consumer review analysis is important for product development, customer satisfaction, competitive advantage, and effective marketing. Increased use of wireless earphones is expected to reach $45.7 billion by 2026 with growth in lifestyle. Therefore, in consideration of the growth and importance of the market, consumer reviews of wireless earphones from Apple and Samsung were analyzed. In this study, 11,320 wireless earphone reviews from Apple and Samsung sold on Coupang were collected to analyze consumers' purchase intentions and analyze consumer satisfaction through analysis of the frequency, sensitivity, and LDA topic model of text mining. As a result of topic modeling, 16 topics were derived and classified into sound quality, connection, shopping mall service, purchase intention, battery, delivery, and price. As a result of brand comparison, Samsung purchased a lot for gift purposes, had a high positive sentiment for price, and Apple had a high positive sentiment for battery, sound quality, connection, service, and delivery. The results of this study can be used as data for related industries as a result of research that can obtain improvements and insights on customer satisfaction, quality and market trends, including manufacturing, retail, marketers, and consumers.

Analyzing TripAdvisor application reviews to enable smart tourism : focusing on topic modeling (스마트 관광 활성화를 위한 트립어드바이저 애플리케이션 리뷰 분석 : 토픽 모델링을 중심으로)

  • YuNa Lee;MuMoungCho Han;SeonYeong Yu;MeeQi Siow;Mijin Noh;YangSok Kim
    • Smart Media Journal
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    • v.12 no.8
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    • pp.9-17
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    • 2023
  • The development of information and communication technology and the improvement of the development and dissemination of smart devices have caused changes in the form of tourism, and the concept of smart tourism has since emerged. In this regard, researches related to smart tourism has been conducted in various fields such as policy implementation and surveys, but there is a lack of research on application reviews. This study collects Trip Advisor application review data in the Google Play Store to identify usage of the application and user satisfaction through Latent Dirichlet Allocation (LDA) topic modeling. The analysis results in four topics, two of which are positive and the other two are negative. We found that users were satisfied with the application's recommendation system, but were dissatisfied when the filters they set during search were not applied or that reviews were not published after updates of the application. We suggest more categories can be added to the application to provide users with different experiences. In addition, it is expected that user satisfaction can be improved by identifying problems within the application, including the filter function, and checking the application environment and resolving the error occurring during the application usage.

Experimental Design of Column Flotation for Recovery of High Grade Molybdenite (고품위 몰리브덴 회수를 위한 컬럼부선 요인설계)

  • Hyun Soo Kim;Purev Oyunbileg;Chul-Hyun Park
    • Resources Recycling
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    • v.32 no.6
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    • pp.34-44
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    • 2023
  • In this work, column flotation using factorial design was performed for recovering high-grade molybdenite concentrate. First, the flotation concentrate from Samyang Mining Plant was regrinded to a mean size of 165, 116, 46.7, and 38.4 ㎛ for an increase of the liberation degree. Tests were carried out for various variables affecting column flotation, and then the concentrates with molybdenite grade and recovery of 98.3 % and 95.28 % were obtained, respectively. Also, regression was performed using the statistical analysis program (SPSS 25) with the factorial design and experimental data on particle size, flow wash-water velocity and depressant that affect high grade. From the results, a model equation was derived to predict the molybdenite grade (MG) and recovery (MR) with the relationship between column flotation variables. Factors such as depressant concentration + wash-water velocity and particle size + depressant concentration + wash-water velocity were smaller than the significance level (0.05) and had a significant effect on the dependent variable, grade, and in the recovery model, only particle size and wash-water velocity factors affected the dependent variable, recovery.

A Study on Electrode Array for Measurement of Induced Polarization of Rock Samples (암석 시료의 유도분극 측정을 위한 전극배열 비교)

  • Man-ho Han;Jung-hwan Lee;Keun-Soo Lee;Myeong-Jong Yi
    • Tunnel and Underground Space
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    • v.33 no.6
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    • pp.483-494
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    • 2023
  • Measurement of the physical properties of rocks or minerals is an important factor in determining the distribution of the underground medium as well as mineral resource investigations. Resistivity and induced polarization, which are widely used in Korea, are methods for measuring electrical properties, which are representative properties of obtaining subsurface information. In order to precisely analyze the exploration data obtained from various sites, it is important to accurately measure the material properties. Electrical properties of rock is measured using two-electrode or four-electrode method. Compared to the four-electrode method, the two-electrode method is generally used because it is very easy to contact the sample and the electrode, but there is a problem in that the impedance of the electrode and the sample is measured together. In this study, the time-domain the induced polarization effects were measured using the 2-electrode method and the 4-electrode method for artificial samples mixed with graphite and cement having induced polarization characteristics, and the results were compared. Although the 4-electrode method has difficulties in installing potential electrodes, it was confirmed that it is effective in measuring electrical properties because it can reduce the problem caused by the impedance of potential electrodes compared to the 2-electrode method.

What's Different about Fake Review? (조작된 리뷰(Fake Review)는 무엇이 다른가?)

  • Jung Won Lee;Cheol Park
    • Information Systems Review
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    • v.23 no.1
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    • pp.45-68
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    • 2021
  • As the influence of online reviews on consumer decision-making increases, concerns about review manipulation are also increasing. Fake reviews or review manipulations are emerging as an important problem by posting untrue reviews in order to increase sales volume, causing the consumer's reverse choice, and acting at a high cost to the society as a whole. Most of the related prior studies have focused on predicting review manipulation through data mining methods, and research from a consumer perspective is insufficient. However, since the possibility of manipulation of reviews perceived by consumers can affect the usefulness of reviews, it can provide important implications for online word-of-mouth management regardless of whether it is false or not. Therefore, in this study, we analyzed whether there is a difference between the review evaluated by the consumer as being manipulated and the general review, and verified whether the manipulated review negatively affects the review usefulness. For empirical analysis, 34,711 online book reviews on the LibraryThing website were analyzed using multilevel logistic regression analysis and Poisson regression analysis. As a result of the analysis, it was found that there were differences in product level, reviewer level, and review level factors between reviews that consumers perceived as being manipulated and reviews that were not. In addition, manipulated reviews have been shown to negatively affect review usefulness.

LDA Topic Modeling and Recommendation of Similar Patent Document Using Word2vec (LDA 토픽 모델링과 Word2vec을 활용한 유사 특허문서 추천연구)

  • Apgil Lee;Keunho Choi;Gunwoo Kim
    • Information Systems Review
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    • v.22 no.1
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    • pp.17-31
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    • 2020
  • With the start of the fourth industrial revolution era, technologies of various fields are merged and new types of technologies and products are being developed. In addition, the importance of the registration of intellectual property rights and patent registration to gain market dominance of them is increasing in oversea as well as in domestic. Accordingly, the number of patents to be processed per examiner is increasing every year, so time and cost for prior art research are increasing. Therefore, a number of researches have been carried out to reduce examination time and cost for patent-pending technology. This paper proposes a method to calculate the degree of similarity among patent documents of the same priority claim when a plurality of patent rights priority claims are filed and to provide them to the examiner and the patent applicant. To this end, we preprocessed the data of the existing irregular patent documents, used Word2vec to obtain similarity between patent documents, and then proposed recommendation model that recommends a similar patent document in descending order of score. This makes it possible to promptly refer to the examination history of patent documents judged to be similar at the time of examination by the examiner, thereby reducing the burden of work and enabling efficient search in the applicant's prior art research. We expect it will contribute greatly.

A Study on Sentiment Score of Healthcare Service Quality on the Hospital Rating (의료 서비스 리뷰의 감성 수준이 병원 평가에 미치는 영향 분석)

  • Jee-Eun Choi;Sodam Kim;Hee-Woong Kim
    • Information Systems Review
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    • v.20 no.2
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    • pp.111-137
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    • 2018
  • Considering the increase in health insurance benefits and the elderly population of the baby boomer generation, the amount consumed by health care in 2020 is expected to account for 20% of US GDP. As the healthcare industry develops, competition among the medical services of hospitals intensifies, and the need of hospitals to manage the quality of medical services increases. In addition, interest in online reviews of hospitals has increased as online reviews have become a tool to predict hospital quality. Consumers tend to refer to online reviews even when choosing healthcare service providers and after evaluating service quality online. This study aims to analyze the effect of sentiment score of healthcare service quality on hospital rating with Yelp hospital reviews. This study classifies large amount of text data collected online primarily into five service quality measurement indexes of SERVQUAL theory. The sentiment scores of reviews are then derived by SERVQUAL dimensions, and an econometric analysis is conducted to determine the sentiment score effects of the five service quality dimensions on hospital reviews. Results shed light on the means of managing online hospital reputation to benefit managers in the healthcare and medical industry.

A Topic Modeling Approach to the Analysis of Seniors' Happiness and Unhappiness in Korea (토픽 모델링 기반 한국 노인의 행복과 불행 이슈 분석)

  • Dong ji Moon;Dine Yon;Hee-Woong Kim
    • Information Systems Review
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    • v.20 no.2
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    • pp.139-161
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    • 2018
  • As Korea became one of the oldest countries in the world, successful aging emerged as an important issue to individuals as well as to society. This study aims to determine not only the Korean seniors' happiness and unhappiness factors but also the means to enhance their happiness and deal with unhappiness. We collected news articles related to the happiness and unhappiness of seniors with nine keywords based on Alderfer's ERG Theory. We then applied a topic modeling technique, Latent Dirichlet Allocation, to examine the main issues underlying the seniors' happiness and unhappiness. According to the analysis, we investigated the conditions of happiness and unhappiness by inspecting the topics based on each keyword. We also conducted a detailed analysis based on the main factors from topic modeling. We proposed specific ways to increase and overcome the happiness and unhappiness of seniors, respectively, in terms of government, corporate, family, and other social welfare organizations. This study indicates the major factors that affect the happiness and unhappiness of seniors. Specific methods to boost happiness and relief unhappiness are suggested from the additional analysis.

A Study on Trends of Key Issues in Port Safety at Busan Port (부산항 항만안전 주요 이슈 동향에 관한 연구)

  • Jeong-Min Lee;Do-Yeon Ha;Joo-Hye Kim
    • Journal of Navigation and Port Research
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    • v.48 no.1
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    • pp.34-48
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    • 2024
  • As global supply chain risks proliferate unpredictably, the high interdependence of port and logistics industry intensifies the risk burden. This study conducted fundamental research to explore diverse safety issues in domestic ports. Utilizing news article data about Busan Port, we employed LDA topic modeling and time-series linear regression to understand key safety trends. Over the past 30 years, Busan Port faced nine major safety issues-maritime safety, import cargo inspection, labor strikes, and natural disasters emerged cyclically. Major port safety issues in Busan Port are primarily characterized by an unpredictable nature, falling under socio-environmental and natural phenomena types, indicating a significant impact of global uncertainty. Therefore, systematic policies need to be formulated based on identified port safety issues to enhance port safety in Busan Port. Additionally, there is a need to strengthen the resilience of port safety for unpredictable risk situations. In conclusion, advanced research activities are necessary to promote port safety enhancement in response to dynamically changing social conditions.

Influence analysis of Internet buzz to corporate performance : Individual stock price prediction using sentiment analysis of online news (온라인 언급이 기업 성과에 미치는 영향 분석 : 뉴스 감성분석을 통한 기업별 주가 예측)

  • Jeong, Ji Seon;Kim, Dong Sung;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.37-51
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    • 2015
  • Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.