• Information Systems Review
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• v.17 no.1
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• pp.49-64
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• 2015

Customer reviews which include subjective opinions for the product or service in online store have been generated rapidly and their influence on customers has become immense due to the widespread usage of SNS. In addition, a number of studies have focused on opinion mining to analyze the positive and negative opinions and get a better solution for customer support and sales. It is very important to select the key terms which reflected the customers' sentiment on the reviews for opinion mining. We proposed a document-level terms-based sentiment classification model by select in the optimal terms with part of speech tag. SVMs (Support vector machines) are utilized to build a predictor for opinion mining and we used the combination of POS tag and four terms extraction methods for the feature selection of SVM. To validate the proposed opinion mining model, we applied it to the customer reviews on Amazon. We eliminated the unmeaning terms known as the stopwords and extracted the useful terms by using part of speech tagging approach after crawling 80,000 reviews. The extracted terms gained from document frequency, TF-IDF, information gain, chi-squared statistic were ranked and 20 ranked terms were used to the feature of SVM model. Our experimental results show that the performance of SVM model with four POS tags is superior to the benchmarked model, which are built by extracting only adjective terms. In addition, the SVM model based on Chi-squared statistic for opinion mining shows the most superior performance among SVM models with 4 different kinds of terms extraction method. Our proposed opinion mining model is expected to improve customer service and gain competitive advantage in online store.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.830-860
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• 2022

[Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.153-173
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• 2022

This study analyzes yelp's online restaurant reviews written in 2019 and explores the factors influencing the decision of the usefulness for online reviews in the restaurant consumption decision process. Specifically, factors expected to affect review usefulness are classified according to the Elaboration Likelihood model. Also, it is assumed that the price range of the restaurant would have a moderating role. For the analysis, datasets provided by yelp.com in February 2020 are used. Among the datasets, online reviews of businesses located in Nevada in the US and belonging to the Food and Restaurant categories are targeted. As a result of the negative binomial regression analysis, it is confirmed that the central cues including review depth and readability and the peripheral cues including review consistency, reviewer popularity, and reviewer exposure positively affect the review usefulness. It is also confirmed that the influences of antecedents that affect the review restaurant prices moderate the effect of the central and peripheral cues on the review usefulness. It also provides implications for the need for price-differentiated review management strategies by review platforms and restaurant businesses.

• Journal of the Korean Society of Food Culture
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• v.28 no.6
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• pp.631-639
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• 2013

The purpose of this study was to analyze the post-purchase behavior of customers who experienced cognitive dissonance after exposure to a franchise foodservice advertisement. The study adopted cognitive dissonance theory to explain the dissonance resulting from the combination of advertisements and actual product that consumers received. In detail, the research hypothesized that cognitive dissonance will affect consumers' post-purchase behavior as well as their efforts to reduce dissonance. Exactly 274 questionnaires were used in the analysis. The results showed that more than 80% of respondents were influenced by advertisements when purchasing menus, and 50% were unsatisfied when the provided menu "was not the same as the advertisement shown". It was found that advertisement type did not significantly affect either group that experienced dissonance. In terms of satisfaction, however, the former group showed greater dissatisfaction when dissonance occurred (p<.001). Finally, there was a significant difference between the two groups regarding post-purchase behavior (p<.05). Customers with dissonance were likely to 'express dissatisfaction directly to the store', 'leave negative reviews', and 'participate in negative word-of-mouth'. Thus, the results revealed that cognitive dissonance could significantly influence customer satisfaction and consequently lead to negative post-purchasing behaviors.

• Journal of Korean Philosophical Society
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• v.143
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• pp.291-313
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• 2017

This article aims to analyze the issue of sexual shame and finding answers for how to solve the problem of unjust shame when victims have suffered shaming in a new direction. While existing philosophical arguments have focused on moderating the negative effects of shame by changing the victims' mind, this article tries to fathom the necessity of how to make offenders feel shame. For this, firstly, characteristics of sexual shame on self are described in brief. And then, the article reviews the problems and limitations of existing philosophical methods which have concentrated on changes of victims' thoughts in order to overcome or prevent the negative effects of unjust sexual shame. Next, considering the liberal political philosophy's argument that it is not appropriate that even offenders who committed wrongs should experience shame as there exists an excessive emphasis on the negative aspects of shame, the overlooked positive aspects of shame on fostering human nature, are analyzed. Finally, in the context of sexual shame, the article explores what sense offenders should feel shame and what justifies shaming them.

• Management & Information Systems Review
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• v.16
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• pp.95-115
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• 2005

Although advertising plays an important role of information source for consumer, also advertising affect negative influence to the consumer and social system. Under the such a concept, this study reviewed the social responsibility of advertising and the freedom of expression including the foreign country's advertising regulation system as the theoretical background of advertising regulation. In addition, this study analyzed the case of the advertisement reviews by Korea Advertising Review Board(august 1, 2000, the business concerning prior deliberation of broadcast advertisements was entrusted to the Korea Advertising Review Board, a civilian self-regulatory body, by the Korean Broadcasting Commission) and Fare Trade Commission. As the result of data analysis, some problems of regulation system and codes are suggested and discussed as follows: (1) the high ratio of rejection (2) using the unnecessary foreign language (3) inconsistency application of deliberation standard.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.1
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• pp.1-9
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• 2018

Ground effect includes a reduction of induced drag, increase of lift, and nose-down moment during landing. These phenomena, occurring late in the landing maneuver, are considered to be of little significance because they tend to counteract and/or compensate in this respect. Even though it is unlikely to affect any flare profile variations appreciably, some pilots have reversed perception about such phenomenon and overestimate during landing. It is becoming a negative factor and is making an adverse effect on landing maneuver. This study examines the perception of ground effect of large aircraft pilots, reviews literature regarding ground effect, and makes suggestions that pilots can correctly recognize and respond to the effect during landing flare maneuvers.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.3
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• pp.371-385
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• 1995

The yield of semiconductor chips is dependent not only on the average defect density but also on the distribution of defects over a wafer. The distribution of defects leads to consider a cluster index. This paper briefly reviews the existing yield prediction models ad proposes a new cluster index, which utilizes the information about the defect location on a wafer in terms of the coefficient of variation. An extensive simulation is performed under a variety of defect distributions and a yield prediction model is derived through the regression analysis to relate the yield with the proposed cluster index and the average number of defects per chip. The performance of the proposed simulation-based yield prediction model is compared with that of the well-known negative binomial model.

• Journal of Korean Society for Quality Management
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• v.27 no.3
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• pp.1-16
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• 1999

According to the study of TQM implementations, the odds that an organization will successfully implement total quality management are two to one-against it. Based on the Brown's study, two thirds of all TQM implementations are dropped or fail altogether. However, organizations armed with knowledge of the factors that have the biggest impact on their success can take steps to influence or change those factors. In this paper, we studied on the degree of influence between those factors and successful start up and alignment factors. Based on extensive literature reviews those factors, threat, commitment, plan, progress and strategy are determined. Also we determine the successful start up and alignment factors. A framework of research including above factors is developed and tested statistically The Perceived data are collected from managers of quality departments of 141 Korean firms through survey. The results show that the rating of those factors which determine success of implementing TQM is progress, commitment, strategy and progress. But the factor of threat shows negative influence for the success of implementing TQM.

• Knowledge Management Research
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• v.10 no.2
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• pp.1-14
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• 2009

This study has investigated the effects of promoting and inhibiting factors on information sharing between buyers and sellers in Korean distribution industry. Based on intensive literature reviews, eight promoting factors(satisfaction, relational norms, trust, commitment, fairness, formalization, participation, transaction specific investment) and five inhibiting factors(opportunism, environmental uncertainty, conflict, concentration, monitoring) were included in the research model. For the purpose of empirical testing, 320 respondents of retailers in Korea were surveyed and the analysis utilizing structural equation model indicated that satisfaction, relational norms, trust, commitment, fairness, formalization, and participation had positive effects on information sharing. And concentration and monitoring had negative effects on it. However transaction specific investment, opportunism, conflict, and environmental uncertainty had no significant effects.