• 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.

• Smart Structures and Systems
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• v.11 no.1
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• pp.19-34
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• 2013

The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified $1^{st}$ mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of $2^{nd}$ mode slope ratio could be used as another feature to indicate imminent pier settlement.

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.167-183
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• 2006

This paper describes a metadata extraction technique based on natural language processing (NLP) which extracts personalized information from email communications between financial analysts and their clients. Personalized means connecting users with content in a personally meaningful way to create, grow, and retain online relationships. Personalization often results in the creation of user profiles that store individuals' preferences regarding goods or services offered by various e-commerce merchants. We developed an automatic metadata extraction system designed to process textual data such as emails, discussion group postings, or chat group transcriptions. The focus of this paper is the recognition of emotional contents such as mood and urgency, which are embedded in the business communications, as metadata.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.652-657
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• 2018

With the rapid development of e-commerce, many customers can now express their opinion on various kinds of product at discussion groups, merchant sites, social networks, etc. Discerning a consensus opinion about a product sold online is difficult due to more and more reviews become available on the internet. Opinion Mining, also known as Sentiment analysis, is the task of automatically detecting and understanding the sentimental expressions about a product from customer textual reviews. Recently, researchers have proposed various approaches for evaluation in sentiment mining by applying several techniques for document, sentence and aspect level. Aspect-based sentiment analysis is getting widely interesting of researchers; however, more complex algorithms are needed to address this issue precisely with larger corpora. This paper introduces an approach of knowledge representation for the task of analyzing product aspect rating. We focus on how to form the nature of sentiment representation from textual opinion by utilizing the representation learning methods which include word embedding and compositional vector models. Our experiment is performed on a dataset of reviews from electronic domain and the obtained result show that the proposed system achieved outstanding methods in previous studies.

• Korean journal of communication and information
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• v.42
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• pp.249-279
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• 2008

This study tried to examine the effect of reading replies on the changes of attitudes towards the subject of online news articles. For that purpose, an experiment was conducted in which participants were asked to read an article and the replies attached. Attitudes were measured before and after reading replies. Another interest of this research was to examine factors affecting the attitude change after reading replies. It was found that while credibility of replies and efficacy belief of the news subject had negative impacts on the attitudes, individuals' information seeking characteristics gave positive impacts on the attitudes after reading replies. This study concludes with discussion and implications of the findings.

• Korean Journal of Health Education and Promotion
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• v.32 no.4
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• pp.13-23
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• 2015

Objectives: his study was performed to examine whether a community organization strategy had been driven by core values explicit in Ottawa Charter and to give some suggestions for using values in health promotion practice in Korea. Methods: We searched literature online with key words of 'values', 'health promotion', and/or 'Ottawa Charter', etc, and reviewed published papers on design, implementation, and evaluation of Health Plus Happiness Plus Projects in Gyeongsangnam-Do, a community organization strategy. Results: Evident core values since Ottawa Charter had been holistic definition of health, empowerment, community participation, addressing the impact of broader determinants of health, reducing social inequities and injustice, and intersectoral collaboration. A community organization strategy was good at realization of most values. Some ways for value-driven health promotion practice were suggested. Conclusions: More discussion and debate on values in health promotion are needed in Korea.

• Journal of Information Science Theory and Practice
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• v.2 no.3
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• pp.29-39
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• 2014

In recent years, several studies have proposed making use of the Twitter micro-blogging service to track various trends in online media and discussion. In this study, we specifically examine the use of Twitter to track discussions of food safety in the Korean language. Given the irregularity of keyword use in most tweets, we focus on optimistic machine-learning and feature set selection to classify collected tweets. We build the classifier model using Naive Bayes & Naive Bayes Multinomial, Support Vector Machine, and Decision Tree Algorithms, all of which show good performance. To select an optimum feature set, we construct a basic feature set as a standard for performance comparison, so that further test feature sets can be evaluated. Experiments show that precision and F-measure performance are best when using a Naive Bayes Multinomial classifier model with a test feature set defined by extracting Substantive, Predicate, Modifier, and Interjection parts of speech.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.1-28
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• 2009

Banking industries have continuously innovated through technology-enhanced products and services. Many studies have recognized the importance of the Internet in banking industries, arguing that it has been widely adopted. Many studies published on the Internet banking in specific countries are mostly related with such issues as internet banking adoption and acceptance, security and risks of online banking system, and interface design. Several studies have been done to examine the differences and similarities between other banking channels and the Internet banking. However, to the best of our knowledge, only a limited number of studies has examined the differences and similarities between two specific countries in order to create a new customer satisfaction model. In this research, we studied the internet banking satisfaction model by comparing two countries: South Korea and Indonesia. We conducted an empirical study based on the data collected in both two countries. In this research, we found that countries which have adopted electric banking services, particularly between a country with high ICT adoption and a country with low ICT adoption, show different satisfaction trends. Based on the study results, herein we provide discussion, managerial, and practical implications.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.169-175
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• 2019

Service quality has been a point of discussion from the decades as it is important for customer satisfaction, loyalty and retention. Various models have been proposed to measure the quality in the service sector. Models are modified in accordance with context and geography to assess the quality of service better. This study aims to investigate the impact of the modified e-SERVQUAL model on the customer perception about the existing relation and potential scope of doing business with a bank which in-turn will decide the performance of the bank. Statistical data was analyzed through various tests like reliability analysis, correlation and regression analysis using SPSS 25.0. The primary data of e-SQ and performance was gathered from 721 internet banking users using 32 item questionnaire, representing 72% response rates, of four selected Islamic banks of Malaysia. E-SERQUAL was modified by adding Shariah Compliance information about banks and products for Islamic banking customers. The finding specified that efficient & reliable services, fulfillment, security/trust, and Shariah compliance information have a significant association with the performance of Islamic banks. The research is original and its implications will be helpful for Islamic banks across the world to enhance the online experience of customers, which will help them to retain the customers in the rapid changing virtual environment.

• The Journal of Information Systems
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• v.29 no.4
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• pp.45-56
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• 2020

Purpose The purpose of this study is to present the direction of efficient e-learning education through the importance and satisfaction survey of learners of non-face-to-face video lectures. Therefore, by grasping the degree of satisfaction of the importance ratio through the IPA analysis method, we try to present improvement measures for insufficient education methods. Design/methodology/approach For IPA analysis, we conducted an online survey of four universities and analyzed 154 samples. The analysis method used SPSS, and through the wordcloud analysis method of R, the suggestions for the non-face-to-face lecture method felt by learners were analyzed to derive implications for improving the quality of education. Findings As a result of the overall satisfaction survey for the entire non-face-to-face class, the factors with the greatest dissatisfaction are listed as follows. Complaints about the adequacy of learning materials and activities (quiz, discussion, assignments, etc.), Complaints about how to use the produced content, and complaints about announcements about class management (lecture schedule, lecture method) were identified in order. The factors of dissatisfaction were clear in the non-face-to-face class where interactive communication was impossible or insufficient. In addition to the lack of quick Q&A, there seems to have been a phenomenon of some neglect.