• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.10-27
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• 2018

The purpose of this study is to explore the meaning of happiness and unhappiness in Korean society through text mining analysis. Similar words with keywords(happiness/unhappiness) from online news portal are extracted using Word2Vec and TF-IDF method. We also use the K-LIWC dictionary to perform the sentiment analysis of words associated with happiness and unhappiness. In TF-IDF analysis, happiness and unhappiness are highly related to social factors and social issues of the year. In Word2Vec analysis, 'Hope' has been similar with happiness for six years. In K-LIWC analysis, 'money/financial issues', 'school', 'communication' is highly related with happiness and unhappiness. In addition, 'physical condition and symptom' is highly related to unhappiness. Implications, limitations, and suggestions for future research are also discussed.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1167-1173
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• 2015

The development of information and communication technology like SNS, blogs, and bulletin boards, was provided a variety of places where you can express your thoughts and comments and allowing Big Data to grow, many people reveal the opinion of the social issues in SNS such as Twitter. In this study, we would like to pre-built sentimental dictionary about social issues and conduct a sentimental analysis with structured dictionary, to gather opinions on social issues that are created on twitter. The data that I used is "bikini", "nakkomsu" including tweet. As the result of analysis, precision is 61% and F1- score is 74%. This study expect to suggest the standard of dictionary construction allowing you to classify positive/negative opinion on specific social issues.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.595-607
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• 2021

Purpose: This study introduces a systematic framework to evaluate service satisfaction of cosmetic brands through online review analysis utilizing Text-Mining technique. Methods: The framework assumes that the service satisfaction is evaluated by positive comments from online reviews. That is, the service satisfaction of a cosmetic brand is evaluated higher as more positive opinions are commented in the online reviews. This study focuses on two approaches. First, it collects online review comments from the top 50 global cosmetic brands and evaluates customer service satisfaction for each cosmetic brands by applying Sentimental Analysis and Latent Dirichlet Allocation. Second, it analyzes the determinants that induce or influence service satisfaction and suggests the guidelines for cosmetic brands with low satisfaction to improve their service satisfaction. Results: For the satisfaction evaluation, online review data were extracted from the top 50 global cosmetic brands in the world based on 2018 sales announced by Brand Finance in the UK. As a result of the satisfaction analysis, it was found that overall there were more positive opinions than negative opinions and the averages for polarity, subjectivity, positive ratio, and negative ratio were calculated as 0.50, 0.76, 0.57, and 0.19, respectively. Polarity, subjectivity and positive ratio showed the opposite pattern to negative ratio, and although there was a slight difference in fluctuation range and ranking between them, the patterns are almost same. Conclusion: The usefulness of the proposed framework was verified through case study. Although some studies have suggested a method to analyze online reviews, they didn't deal with the satisfaction evaluation among competitors and cause analysis. This study is different from previous studies in that it evaluates service satisfaction from a relative point of view among cosmetic brands and analyze determinants.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.67-77
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• 2021

This study conducted topic modeling, association analysis, and sentiment analysis focused on text mining in order to reflect regional characteristics in the process of establishing an information plan in Chungcheongbuk-do. As a result of the analysis, it was confirmed that Chungcheongbuk-do occupies a relatively high proportion of educational activities to bridge the information gap, and is interested in improving infrastructure to provide non-face-to-face, untouched administrative services, and bridge the gap between urban and rural areas. In addition, it is necessary to refer to the fact that there is a positive evaluation of the combination of bio and IT in the regional strategic industry and examples of ICT innovation services. It has been confirmed that smart cities have high expectations for the establishment of various cooperation systems with IT companies, but continuous crisis management is necessary so that they are not related to political issues. It is hoped that the results of this study can be used as one of the methods to specifically reflect regional changes in the process of informatization.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.30-40
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• 2021

Ratings and reviews, despite their growing influence on restaurants' sales and reputation, entail a few limitations due to the burgeoning of reviews and inaccuracies in rating systems. This study explores the texts in reviews and ratings of a delivery application and discovers ways to elevate review credibility and usefulness. Through a text mining method, we concluded that the delivery application 'Yogiyo' has (1) a five-star oriented rating dispersion, (2) a strong positive correlation between rating factors (taste, quantity, and delivery) and (3) distinct part of speech and morpheme proportions depending on review polarity. We created a chicken-specialized negative word dictionary under four main topics and 20 sub-topic classifications after extracting a total of 367 negative words. We provide insights on how the research on delivery app reviews should progress, centered on fried chicken reviews.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.787-797
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• 2023

The use of service robots, particularly guide robots, is becoming increasingly prevalent in public institutions. However, there has been limited research into the interactions between users and guide robots. To explore the customer experience with the guidance robot, we selected 'QI', which has been meeting customers for the longest time, and collected all reviews since the service was launched in public institutions. By using text mining techniques, we identified the main keywords and user experience factors and examined factors that hinder user experience. As a result, the guide robot's functionality, appearance, interaction methods, and role as a cultural commentator and helper were key factors that influenced the user experience. After identifying hindrance factors, we suggested solutions such as improved interaction design, multimodal interface service design, and content development. This study contributes to the understanding of user experience with guide robots and provides practical suggestions for improvement.

• Annual Conference of KIPS
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• 2014.04a
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• pp.745-748
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• 2014

SentiWordNet is an important lexical resource supporting sentiment analysis in opinion mining applications. In this paper, we propose a novel approach to construct a Vietnamese SentiWordNet (VSWN). SentiWordNet is typically generated from WordNet in which each synset has numerical scores to indicate its opinion polarities. Many previous studies obtained these scores by applying a machine learning method to WordNet. However, Vietnamese WordNet is not available unfortunately by the time of this paper. Therefore, we propose a method to construct VSWN from a Vietnamese dictionary, not from WordNet. We show the effectiveness of the proposed method by generating a VSWN with 39,561 synsets automatically. The method is experimentally tested with 266 synsets with aspect of positivity and negativity. It attains a competitive result compared with English SentiWordNet that is 0.066 and 0.052 differences for positivity and negativity sets respectively.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.225-226
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• 2019

오피니언 마이닝은 온라인 문서의 감성을 추출하여 분석하는 기법이다. 별도의 여론조사 없이 감성을 분석 가능하므로, 최근 활발한 연구 분야이다. 그러나 소셜미디어에는 신조어 등이 많이 포함되어 있어 기존 감성분석 시스템으로는 정확한 분석이 어려울 뿐만 아니라, 복합적인 감성에 대한 분석을 내리기에 불리하다. 이에 본 연구에서는 직관적인 감성모델을 제안하고 SNS에서 주목받는 다양한 신조어를 수용한 감성단어사전을 구축한 후, 이를 적용하여 소셜미디어에 나타나는 복합적인 감성을 분석하는 감성분석시스템을 설계한다.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1029-1035
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• 2019

In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate movie-based recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

• Annual Conference on Human and Language Technology
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• 2019.10a
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• pp.429-433
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• 2019

스마트폰 보급의 확산으로 제품 구매 시 웹 사이트 및 SNS를 이용하여 제품 리뷰를 참고하는 소비자들이 증가하고 있다. 전자 상거래 사이트의 제품 리뷰는 구매 예정자들에게 유용한 정보로 활용되곤 한다. 하지만 구매 예정자가 직접 제품에 대한 리뷰 데이터를 찾아 전체 내용을 일일이 읽고 분석해야하기 때문에 시간이 오래 걸릴뿐만 아니라 가공되지 않는 데이터가 줄 수 있는 정보는 한정적이다. 또한 이러한 리뷰들은 상품의 특징을 파악하기에도 어려움이 있다. 본 논문에서는 제품의 주요 이슈를 추출하고 주요 이슈에 대한 감성 분석과 감성 요약을 통해 제품 분석 및 평가를 제공하는 시스템을 설계 및 구현하였다. 이를 휴대폰 제품에 적용하여 구축한 시스템을 통해 소비자가 방대한 양의 제품의 리뷰 데이터를 분석할 필요 없이 제품의 주요 이슈와 가공된 분석 결과를 시각적으로 빠르게 제공받을 수 있음을 보였다.