• Journal of the Korean Home Economics Association
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• v.41 no.11
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• pp.189-200
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• 2003

The purpose of this study was to investigate that positive and negative word-of-mouth informations getting hairshop customers have influence on visiting intention of potential consumers. Data were collected from 354 university or college women. The results showed as follows; First, positive word-of-mouth informations that consumers have experienced in using hairshop were employee altitude/technique, consideration in customer's situation, kindness, saving of time/additional service, facilities, rational price, gift service/benefit in conditions of location. Second, negative word-of-mouth informations that consumers have experienced in using hairshop were inconsistent service, service focus on non-customers, irrational price/technique insufficiency/ inadequate compensational system, irrelevance of face-to-face management. Third, in getting positive word-of-mouth informations, consideration in customer's situation, rational price and gift service/benefit in conditions of location, consumers had visiting intention, and in getting negative informations, irrational price/technique insufficiency/inadequate compensational system, consumers had no visiting intention.

• The Journal of Information Systems
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• v.30 no.1
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• pp.45-64
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• 2021

Purpose The traditional topic modeling technique makes it difficult to distinguish the semantic of topics because the key words assigned to each topic would be also assigned to other topics. This problem could become severe when the number of online reviews are small. In this paper, the extended model of topic modeling technique that can be used for analyzing a small amount of online reviews is proposed. Design/methodology/approach The extended model of being proposed in this paper is a form that combines the traditional topic modeling technique and the Word2Vec technique. The extended model only allocates main words to the extracted topics, but also generates discriminatory words between topics. In particular, Word2vec technique is applied in the process of extracting related words semantically for each discriminatory word. In the extended model, main words and discriminatory words with similar words semantically are used in the process of semantic classification and naming of extracted topics, so that the semantic classification and naming of topics can be more clearly performed. For case study, online reviews related with Udo in Tripadvisor web site were analyzed by applying the traditional topic modeling and the proposed extension model. In the process of semantic classification and naming of the extracted topics, the traditional topic modeling technique and the extended model were compared. Findings Since the extended model is a concept that utilizes additional information in the existing topic modeling information, it can be confirmed that it is more effective than the existing topic modeling in semantic division between topics and the process of assigning topic names.

• International Journal of Contents
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• v.8 no.3
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• pp.71-78
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• 2012

The emergence of the Internet has provided a new outlet for consumers who experience service failure from products and services, augmenting the traditional options of entry, voice and action. Consumers' negative word of mouth through online (word-of-mouse or eWOM) far exceeds traditional word of mouth (WOM) in respect of its potential effectiveness, speed and spread. This paper tries to figure out the service failure themes in the health care industry by analyzing online word-of-mouse using the critical incidents technique (CIT). Complaint themes in the area of healthcare are identified and analyzed. The results identify that major complaint theme differed according to the site type. Also, the findings indicate that delivery and customer services are critical issues when consumer makes negative WOM.

• The Journal of Information Systems
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• v.28 no.3
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• pp.105-121
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• 2019

Purpose One of the reasons for the expansion of information systems in the enterprise is the increased efficiency of data analysis. In particular, the rapidly increasing data types which are complex and unstructured such as video, voice, images, and conversations in and out of social networks. The purpose of this study is the customer needs analysis from customer voices, ie, text data, in the web environment.. Design/methodology/approach As previous study results, the word frequency of the sentence is extracted as a word that interprets the sentence has better affects than frequency analysis. In this study, we applied the TF-IDF method, which extracts important keywords in real sentences, not the TF method, which is a word extraction technique that expresses sentences with simple frequency only, in Korean language research. We visualized the two techniques by cluster analysis and describe the difference. Findings TF technique and TF-IDF technique are applied for Korean natural language processing, the research showed the value from frequency analysis technique to semantic analysis and it is expected to change the technique by Korean language processing researcher.

• Asian Journal of Business Environment
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• v.6 no.3
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• pp.21-31
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• 2016

Purpose - The purpose of this research is to determine the impact of word of mouth on customer perceived value for restaurants in Malaysia. The objectives of this research include determining how word of mouth (WoM) factors - frequency of word of mouth messages, reputation of word of mouth messenger, richness of word of mouth message, dispersion of word of mouth conversations and manner of word of mouth delivery impact customer perceived value in Malaysian restaurant industry. Research Design, Data, and Methodology - The research follows causal / explanatory research method based on quantitative data. A sample of 150 restaurant customers in Kuala Lumpur, Malaysia was selected using convenience sampling technique. Likert scale questionnaire is used to collect data and data is analysed using regression analysis through SPSS 22. Results - The statistical analysis revealed that independent variable 'manner of delivery' significantly and positively impacts customer perceived value for restaurants in Malaysia. Conclusions - To build strong positive customer perception, Malaysian restaurants can enhance word of mouth campaigns' 'manner of delivery' by making them passionate, exciting and with high emotional appeal.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.299-303
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• 2009

Patent information search is used for checking existence of earlier works. In patent information search, there are many reasons that fails to get appropriate information. This research proposes a method extracting alternative word candidates in order to minimize search failure due to keyword mismatch. Assuming that two words have similar meaning if they have similar co-occurrence words, the proposed method uses the concept of concentration, association word set, cosine similarity between association word sets and a ranking modification technique. Performance of the proposed method is evaluated using a manually extracted alternative word candidate list. Evaluation results show that the proposed method outperforms the document vector space model in recall.

• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.171-181
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• 2001

The previous Bayesian document categorization method has problems that it requires a lot of time and effort in word clustering and it hardly reflects the semantic information between words. In this paper, we propose a weighted Bayesian document categorizing method based on association word knowledge base acquired by mining technique. The proposed method constructs weighted association word knowledge base using documents in training set. Then, classifier using Bayesian probability categorizes documents based on the constructed association word knowledge base. In order to evaluate performance of the proposed method, we compare our experimental results with those of weighted Bayesian document categorizing method using vocabulary dictionary by mutual information, weighted Bayesian document categorizing method, and simple Bayesian document categorizing method. The experimental result shows that weighted Bayesian categorizing method using association word knowledge base has improved performance 0.87% and 2.77% and 5.09% over weighted Bayesian categorizing method using vocabulary dictionary by mutual information and weighted Bayesian method and simple Bayesian method, respectively.

• Journal of Distribution Science
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• v.20 no.7
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• pp.87-95
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• 2022

Purpose: This study aims to analyze the effects of Brand Coolness, Brand Love, and Self-brand Connections on Word-of-mouth positively. The retail format of Starbuck in Vietnam is successful in distribution applied when it becomes the place for customers to express themselves. Consumers are now aware about Brand Coolness of the Starbucks developed in Vietnam then turn to love the brand of store and connect themselves to the brand. In this study, the closest relationship to form the basis for consumer Word-of-mouth about a brand is the relationship between Brand Coolness and Brand Love. Results: The findings show that Brand Coolness and Brand Love are important value factors in customers' minds toward their behavior, form there, it will contribute to the brand store in distribution. Research design, data and methodology: This article used the quantitative technique utilizing PLS-SEM software to test the hypothesis with 600 samples. The data obtained shows that people have Word-of-mouth about the retail format of Starbucks in Ho Chi Minh City. Conclusion: The study has demonstrated the conclusions and proposed solutions to help beverage brands build Brand Love, thereby achieving coolness, connecting brands with themselves, leading to customer Word-of-mouth in a positive way towards retail format.

• Korean Journal of Cognitive Science
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• v.19 no.1
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• pp.17-39
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• 2008

The present study was conducted to provide Korean word association lists for adults and children which are needed in research area of false memory. Associated words, asso[iation strength, and the proportion of cue set size to the total number of associated words produced through the discrete association technique were compared between the two groups. The data showed that associated words with high strength wert same or similar but associated words with lower strength were various in the two groups. The result that adults produced larger proportion of cue set size than children suggests that adults have more typical and more convergent semantic network than children. The present data will be served as a database useful for the studies to investigate cognitive functions in memory and other related area.

• Journal of KIISE:Software and Applications
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• v.36 no.10
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• pp.861-873
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• 2009

There are many reasons that fail to get appropriate information in information retrieval. Allomorph is one of the reasons for search failure due to keyword mismatch. This research proposes a method to construct alternative word candidates automatically in order to minimize search failure due to keyword mismatch. Assuming that two words have similar meaning if they have similar co-occurrence words, the proposed method uses the concept of concentration, association word set, cosine similarity between association word sets and a filtering technique using confidence. Performance of the proposed method is evaluated using a manually extracted alternative list. Evaluation results show that the proposed method outperforms the context window overlapping in precision and recall.