• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.173-178
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• 2021

In this paper, we find a suitable methodology for Korean Sentiment Analysis through a comparative experiment in which methods of embedding and natural network models are learned at the highest accuracy and fastest speed. The embedding method compares word embeddeding and Word2Vec. The model compares and experiments representative neural network models CNN, RNN, LSTM, GRU, Bi-LSTM and Bi-GRU with IKEA review data. Experiments show that Word2Vec and BiGRU had the highest accuracy and second fastest speed with 94.23% accuracy and 42.30 seconds speed. Word2Vec and GRU were found to have the third highest accuracy and fastest speed with 92.53% accuracy and 26.75 seconds speed.

• Journal of Korean Academy of Nursing Administration
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• v.10 no.2
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• pp.195-210
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• 2004

Purpose: The purpose of this study is 1): to investigate how word of mouth communications work according to the lifestyle of health care consumers of obstetrics and gynecology, 2): to propose managerial suggestions in health care marketing. Method: Data collection and analysis had been executed from March 10, 2003 to April 4, 2003. Out of total 400 questionnaires distributed, 385 were collected. 351 were considered to be valid for analysis. Data were analyzed with the SPSS/pc+ Version 10.0. using Frequencies, Factor analysis and cluster analysis, ANOVA and $x^2-test$. Results: The subjects were divided into four groups in terms of their lifestyles: 'health active group', 'health conscious group', 'health indifferent group', 'health inactive group'. The following are the features word of mouth communication according to lifestyle. Conclusion: All in all, the researcher carne to notice that there was a difference in the features of word of mouth communication activities in accordance with the lifestyle of health care consumers of obstetrics and gynecology. This study will hopefully contribute to the ramification of markets, serving as a help in marketing health services.

• Journal of Fashion Business
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• v.13 no.5
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• pp.110-120
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• 2009

The goal of this study was to investigate the influence of customer service quality on customer satisfaction. Also the object of this study is to indicate the influence on word of mouth and intention of repurchase which is a variable of customer satisfaction. The subjects were 357 female adults living in Suncheon City, Jeollanam Province. The questionnaires were conveniently sampled from June 1 to 30, 2006. The collected data was analyzed by percentage, frequency, mean, factor analysis, reliability, regression using the SPSS program. The five hypotheses set in the research model, all were selected through empirical analysis. Main findings are as follows: As a result of factor analysis, customer service quality of discount store verified four items, that is, personal service, VMD of stores/atmosphere, store policy, product assortment. As a result of regression analysis, customer service quality influenced customer satisfaction. The intention of repurchase and word of mouth received a positive influence from customer satisfaction. The intention of repurchase influenced the word of mouth, and it received a positive influence from the word of mouth.

• Korean Management Science Review
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• v.23 no.3
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• pp.77-93
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• 2006

In the highly competitive world, there has been a concomitant increase in the need for the research and planning methodology, which can perform an advanced assessment of technological opportunities and an early Perception of threats and possibilities of the emerging technology according to the nation's economic and social status. This research is aiming to provide indicators and visualization methods to measure the latest research trend and aspect underlying scientific and technological documents to researchers and policy planners using 'Co-word Analysis' Organic light emitting diodes(OLED) is an emerging technology in various fields of display and which has a highly prospective market value. In this paper, we presented an analysis on OLED. Co-word analysis was employed to reveal patterns and trends in the OLED fields by measuring the association strength of terms representatives of relevant publications or other texts produced in the OLED field. Data were collected from SCI and the critical keywords could De extracted from the author keywords. These extracted keywords were further standardized. In order to trace the dynamic changes in the OLED field, we presented a variety of technology mapping. The results showed that the OLED field has some established research theme and also rapidly transforms to embrace new themes.

• The Journal of Information Systems
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• v.31 no.4
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• pp.189-207
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• 2022

Purpose Previous research on customer engagement in SNS marketing has mainly addressed the conceptualization of type of word-of-mouth messages. However, there is a lack of researches about the effect of the brand-page characteristics on the type of word-of-mouth messages. Therefore, this study examined the effect of brand-page characteristics in terms of the type of word-of-mouth messages as the main objective and the effect of the type of word-of-mouth messages in terms of the brand loyalty as the secondary objective in the context of Facebook. Design/methodology/approach The empirical research was based on a poll done through 400 research candidates in the Facebook and the final 342 responses were collected and used in statistical data analysis. The adaptability, trust, and validity to measurement model were verified and the structural relationship in the research model was analyzed through these 342 responses. The collected data verified hypotheses established using the SPSS statistical package and structural equation model using AMOS. Findings The results showed that the BP-information provision had a non-significant effect on the factual word-of-mouth message and a significant effect on the evaluative word-of-mouth message. The BP-reliability had a significant effect on the factual word-of-mouth message and the evaluative word-of-mouth message. The BP-entertainment had a significant effect on the factual word-of-mouth message and the evaluative word-of-mouth effect. The BP-interaction had a non-significant effect on the factual word-of-mouth message and the evaluative word-of-mouth message. Finally, the factual word-of-mouth message and the evaluative word-of-mouth message had a significant effect on the brand loyalty.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1586-1593
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• 2010

Vocabulary recognition error correction method has probabilistic pattern matting and dynamic pattern matting. In it's a sentences to based on key-word by semantic analysis. Therefore it has problem with key-word not semantic analysis for morphological changes shape. Recognition rate improve of vocabulary unrecognized reduced this paper is propose. In syllable restoration algorithm find out semantic of a phoneme recognized by a phoneme semantic analysis process. Using to sentences restoration that morphological analysis and morphological analysis. Find out error correction rate using phoneme likelihood and confidence for system parse. When vocabulary recognition perform error correction for error proved vocabulary. system performance comparison as a result of recognition improve represent 2.0% by method using error pattern learning and error pattern matting, vocabulary mean pattern base on method.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.2
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• pp.172-178
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• 2015

Constructing a bilingual multi-word lexicon is confronted with many difficulties such as an absence of a commonly accepted gold-standard dataset. Besides, in fact, there is no everybody's definition of what a multi-word unit is. In considering these problems, this paper evaluates and analyzes the context vector approach which is one of a novel alignment method of constructing bilingual lexicons from parallel corpora, by comparing with one of general methods. The approach builds context vectors for both source and target single-word units from two parallel corpora. To adapt the approach to multi-word units, we identify all multi-word candidates (namely noun phrases in this work) first, and then concatenate them into single-word units. As a result, therefore, we can use the context vector approach to satisfy our need for multi-word units. In our experimental results, the context vector approach has shown stronger performance over the other approach. The contribution of the paper is analyzing the various types of errors for the experimental results. For the future works, we will study the similarity measure that not only covers a multi-word unit itself but also covers its constituents.

• Journal of The Korean Association For Science Education
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• v.40 no.1
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• pp.41-50
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• 2020

Looking at the understanding of scientific concepts from a linguistic perspective, it is very important for students to develop a deep and sophisticated understanding of words used in scientific concept as well as the ability to use them correctly. This study intends to provide the basis for productive knowledge education of scientific words by noting that the foundation of productive knowledge teaching on scientific words is not well established, and by exploring ways to teach the relationship among words that constitute scientific concept in a productive and effective manner. To this end, we extracted the relationship among the words that make up the scientific concept from the text of science textbook by using quantitative text analysis methods, second, qualitatively examined the meaning of the word relationship extracted as a result of each method, and third, we proposed a writing activity method to help improve the productive knowledge of scientific concept words. We analyzed the text of the "Force and motion" unit on first grade science textbook by using four methods of quantitative linguistic analysis: word cluster, co-occurrence, text network analysis, and word-embedding. As results, this study suggests four writing activities, completing sentence activity by using the result of word cluster analysis, filling the blanks activity by using the result of co-occurrence analysis, material-oriented writing activities by using the result of text network analysis, and finally we made a list of important words by using the result of word embedding.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.148-150
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• 2017

In recent years, "altmetrics", given birth by social media and the academic community, have become a metric source for measuring the academic impact of scientific literature. This study has undertaken a co-word analysis of author keywords in "Altmetrics" articles from the Web of Science database from 2012 to 2017 and used a co-occurrence matrix to create a clustering of the words. "Altmetrics" co-occurrence network map was derived and the research hotspots was analyzed.

• Journal of Contemporary Eastern Asia
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• v.16 no.2
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• pp.110-144
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• 2017

Unlike most languages, written Chinese has no spaces between words. Word segmentation must be performed before semantic network analysis can be conducted. This paper describes how to perform Chinese word segmentation using the Stanford Natural Language Processing group's Stanford Word Segmenter v. 3.8.0, released in June 2017.