• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.3
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• pp.293-304
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• 2014

This study investigated the effect of consumers' shopping value in social commerce on consumers' fashion shopping satisfaction and future behavioral intention. Respondents were limited to consumers aged 20 to 39 who had recently purchased fashion products through social commerce over the last month. The final analysis used 318 samples. Descriptive statistics, Cronbach's alpha, confirmatory factor analysis, and structural equation model were conducted. The results are as follows. First, hedonic and utilitarian shopping value significantly influenced consumers' fashion shopping satisfaction in social commerce. Hedonic shopping value was more strongly related to fashion shopping satisfaction. Second, fashion shopping satisfaction in social commerce had an effect on behavioral intention and SNS word-of-mouth. Behavioral intention consisted of repurchase intention and recommend intention. SNS word-of-mouth intention represented word-of-mouth intention using SNS such as Facebook and Twitter. When consumers were satisfied with their shopping experience, they were willing to have re-patronage intentions and SNS word-of-mouth intention. The results suggested that social commerce should try to raise consumers' fashion shopping satisfaction in social commerce and offer a pleasant experience. Also, social commerce should try to be connected to SNS such as Facebook and Twitter to increase word-of-mouth intention.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Culinary science and hospitality research
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• v.14 no.4
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• pp.188-202
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• 2008

The purpose of this research was to investigate the effects of various restaurant choice attributes on customer satisfaction that has positive influence on repatronage and word of mouth intent. This study examined relevant literatures, set up some hypotheses to solve main questionable considerations and made a corresponding empirical analysis. For the empirical analysis, a questionnaire survey was applied to total 478 customers who had visited restaurants around the northern part of Gyeong-gi province. The model was tested using SPSS 12.0 and AMOS 5.0 with 472 samples which received a 99% usable response rate. The results of empirical analysis were as follows: 1) menu quality has a significant effect on customer satisfaction and word of mouth intent. 2) service quality and convenience have a significant effect on customer satisfaction. 3) customer satisfaction has a significant effect on repatronage and word of mouth intent. 4) word of mouth intent has a significant effect on repatronage intent.

• Journal of Forest and Environmental Science
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• v.34 no.1
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• pp.46-49
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• 2018

This study aims to explore the knowledge structure of the leopard cat (Prionailurus bengalensis) research during the period of 1952-2017. Data was collected from Google Scholar and Research Information Service System (RISS), and a total of 482 author keywords from 125 papers from peer-reviewed scholarly journals were retrieved. Co-word analysis was applied to examine patterns and trends in the leopard cat research by measuring the association strengths of the author keywords along with the descriptive analysis of the keywords. The result shows that the most commonly used keywords in leopard cat research were Felidae, Iriomte cat, and camera trap except for its English and scientific name, and camera traps became a frequent keyword since 2005. Co-word analysis also reveals that leopard cat research has been actively conducted in Southeast Asia in conjugation with studying other carnivores using the camera traps. Through the understanding of the patterns and trends, the finding of this study could provide an opportunity for the exploration of neglected areas in the leopard cat research and conservation.

• The Journal of Korean Association of Computer Education
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• v.17 no.6
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• pp.115-122
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• 2014

One of the problems with current youth generations is increasing rate of violence and suicide in their school lives, and this study aims at the design of a sentiment analysis system to prevent suicide by uising big data process. The main issues of the design are economical implementation, easy and fast processing for the users, so, the open source Hadoop system with MapReduce algorithm is used on the HDFS(Hadoop Distributed File System) for the experimentation. This study uses word count method to do the sentiment analysis with informal data on some sns communications concerning a kinds of violent words, in terms of text mining to avoid some expensive and complex statistical analysis methods.

• Journal of Fashion Business
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• v.27 no.4
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• pp.50-66
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• 2023

The purpose of this study was to examine the word distribution and topic distribution of slow fashion appearing on YouTube in detail and identify the characteristics and aspects related to fashion design through big data analysis and content analysis methods. The specific research results were as follows. First, in the results of the word distribution analysis, "item" appeared the most, 203 times. Also, "one-piece" was a point to pay attention to, as the item had the highest frequency. Second, a total of 5 topics were defined in the topic distribution analysis: topic 1 was "vintage products," topic 2 was "fashion items," topic 3 was "eco-friendly," topic 4 was "life quality emphasis," and topic 5 was "prudent consumption." Third, looking at the relationship between word distribution and topic distribution above, Korean slow fashion on YouTube was actively selecting related design elements that express vintage images in clothing life regardless of trends. In addition, there was a tendency to pursue various basic and high-quality items. Other than those findings, basic items tended to be reinterpreted in various ways through styling methods matched to the vintage image. Lastly, the tendency of slow and small-volume production appeared to emphasize handicrafts and the cultural values of fashion products.

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.620-629
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• 2019

An automated minutes summary system is required to objectively summarize and classify the contents of discussions or discussions for decision making. This paper designs and implements a minutes summary system using word2vec model to complement the existing minutes summary system. The proposed system is further implemented with word2vec model to remove index words during morpheme analysis and to extract representative sentences with common opinions from documents. The proposed system automatically classifies documents collected during the meeting process and extracts representative sentences representing the agenda among various opinions. The conference host can quickly identify and manage all the agendas discussed at the meeting through the proposal system. The proposed system analyzes various agendas of large-scale debates or discussions and summarizes sentences that can be representative opinions to support fast and accurate decision making.

• Journal of Korean Academy of Nursing
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• v.10 no.2
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• pp.21-40
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• 1980

In order to take cue of the dying persons and their survivors in a more positive and affirmative atti-tube. and to understand the valuable meaning of and dying. a survey was performed to 550 cases of health care personnels including 116 nursing students. 238 medical students. 137 nurses. and 59 doctors. Samplings were made through census Procedure from the entire group of medical and nursing students in College of Medicine. Chung-Ang University. and of licenced nurses and doctors in Chung-Ang University Hospital. and in Han-Gang Sacred Heart Hospital from the first to the end of march. 1980. These collected data were computerized at KIST by SPSS programming and were statistically analyzed by chi-square test. Through content analysis of the word associated with death and descriptive analysis of the death-re-lated variables. the following conclusion in is reached. First. Total numbers of death-word percieved by health care personnels were 198 kinds. Among them, 40 kinds of words associated with death were responded from than 1% of the total. As to the 10 death related word responded by free word association method. it was revealed that individual average number of death related word was 7.70 word. which came from higher number of words in the senior students (8.96 word) or the graduates (8.10 word) compared with the freshman (6.84 word). Second. In Content specific analysis of the death related word. more frequently perceived types summarized as the following order; the affective context of death. the diseases. the disasters. the religion, the funeral ceremonies. the separation, the drakness. and the life. Third. The most prevalent 10 words associated with death which the the respondents gave response to the the first recalling word. were as following o order； the dieases. the sadness, the vanity. the darkness, the frustration. the suicide. the incurable dieases, the graves. the dead. and the catastrophes. By sex, the diease is outstanding in females, but the vanity is in males. By occupation. the vanity and the dead was frequently observed in student group including senior students. while the incurable dieases presented by doctors. Fourth. In health care personnels. the first perceived ages of death were 11.47 $\pm$3.33 years (8.14- 15.80 years). Among them. senior students were inclined to percept death at the earliest age of life (11.28years). while doctors and nurses perceived death later in their life (12.98 years). Fifth, It is revealed in this survey that the most frequently responded death perceiving motives by health care personnels ar“psychological conflict”and“death of those around them”. Death perceiving motives can be classified in two factors; personality and life circumstances. Sixth It is of interest that only 11.3% health care personnels was found to feel death as inevitable or acceptable event. whereas 58.3% deny or reject it.

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.181-194
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• 2019

The purpose of this study is to investigate the effect of physical environment of Japanese restaurant on customer satisfaction, revisit intention and word of mouth intention. For this purpose, data were collected from 341 adult males and females who had used Japanese restaurants in Daegu. SPSS program frequency analysis, factor analysis, regression analysis and multiple regression analysis were used for data analysis. Through the factor analysis, the physical environment of the Japanese specialty restaurant was identified as a component of comfort, aesthetics, and convenience. As a result of the multiple regression analysis, the three components of the physical environment have positive effects on customer satisfaction, return visit intention, and word of mouth intention. The results of regression analysis showed that customer satisfaction had a positive effect on revisit and word of mouth intention. Through the results of this study, we confirmed the physical and environmental impacts of the specialty restaurants and suggested the practical and theoretical implications.

• Fashion & Textile Research Journal
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• v.7 no.2
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• pp.218-224
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• 2005

The purpose of this study was to investigate the infiluence of positive and negative word-of-mouth informations on visiting intention of hairshop customers. Data were collected from 342 adult females and analyzed by using frequencies, factor analysis and regression utilizing SPSS/PC+. The results showed that positive word-of-mouth informations such as shop employees' skill/attitudes, physical benefit, comfortable facilities, time saving/consistent service, kindness and rational price had influence on the visiting intention of hairshop customers. The negative word-of-mouth informations that consumers had experienced using hairshop were categorized as untrustworthy face-to-face customer management, non-customer service oriented mind, and unskilled employees/inefficient hairshop environment. The negative word-of-mouth informations had no effect on the visiting intention.