• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.23-43
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• 2016

As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.721-722
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• 2009

인터넷 시장이 빠르게 성장함에 따라 사용자들의 참여도가 매우 높아졌다. 인터넷 사용자들은 시장의 상품과 더불어 영화와 같은 문화 생활에 관한 의견을 웹 상에 표현하기 시작했고, 현재에 들어 그 양이 방대해 졌다. 본 논문에서는 사용들이 작성한 영화에 관한 리뷰를 모아 방대한 양에서 유용한 정보를 효율적으로 도출하고 요약해서 사용자에게 제공하는 방법을 제안한다.

• Journal of KIISE
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• v.42 no.4
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• pp.512-521
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• 2015

Internet users purchase goods on the Internet and express their positive or negative emotions of the goods in product reviews. Analysis of the product reviews become critical data to both potential consumers and to the decision making of enterprises. Therefore, the importance of opinion mining techniques which derive opinions by analyzing meaningful data from large numbers of Internet reviews. Existing studies were mostly based on comments written in English, yet analysis in Korean has not actively been done. Unlike English, Korean has characteristics of complex adjectives and suffixes. Existing studies did not consider the characteristics of the Internet language. This study proposes an emotional classification method which increases the accuracy of emotional classification by analyzing the characteristics of the Internet language connoting feelings. We can classify positive and negative comments about products automatically using the Internet emoticon. Also we can check the validity of the proposed algorithm through the result of high precision, recall and coverage for the evaluation of this method.

• Asia Marketing Journal
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• v.13 no.4
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• pp.159-189
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• 2012

What attracts consumers to bloggers' reviews? Consumers would be attracted both by the Bloggers' expertise (i.e., knowledge and experience) and by his/her unbiased manner of delivering information. Expertise and trustworthiness are both virtues of information sources, particularly when there is uncertainty in decision-making. Noting this point, we postulate that consumers' motives determine the relative weights they place on expertise and trustworthiness. In addition, our hypotheses assume that tie strength moderates consumers' expectation on bloggers' expertise and trustworthiness: with expectation on expertise enhanced for power-blog user-group (weak-ties), and an expectation on trustworthiness elevated for personal-blog user-group (strong-ties). Finally, we theorize that the effect of credibility on willingness to accept a review is moderated by tie strength; the predictive power of credibility is more prominent for the personal-blog user-groups than for the power-blog user groups. To support these assumptions, we conducted a field survey with blog users, collecting retrospective self-report data. The "gourmet shop" was chosen as a target product category, and obtained data analyzed by structural equations modeling. Findings from these data provide empirical support for our theoretical predictions. First, we found that the purposive motive aimed at satisfying instrumental information needs increases reliance on bloggers' expertise, but interpersonal connectivity value for alleviating loneliness elevates reliance on bloggers' trustworthiness. Second, expertise-based credibility is more prominent for power-blog user-groups than for personal-blog user-groups. While strong ties attract consumers with trustworthiness based on close emotional bonds, weak ties gain consumers' attention with new, non-redundant information (Levin & Cross, 2004). Thus, when the existing knowledge system, used in strong ties, does not work as smoothly for addressing an impending problem, the weak-tie source can be utilized as a handy reference. Thus, we can anticipate that power bloggers secure credibility by virtue of their expertise while personal bloggers trade off on their trustworthiness. Our analysis demonstrates that power bloggers appeal more strongly to consumers than do personal bloggers in the area of expertise-based credibility. Finally, the effect of review credibility on willingness to accept a review is higher for the personal-blog user-group than for the power-blog user-group. Actually, the inference that review credibility is a potent predictor of assessing willingness to accept a review is grounded on the analogy that attitude is an effective indicator of purchase intention. However, if memory about established attitudes is blocked, the predictive power of attitude on purchase intention is considerably diminished. Likewise, the effect of credibility on willingness to accept a review can be affected by certain moderators. Inspired by this analogy, we introduced tie strength as a possible moderator and demonstrated that tie strength moderated the effect of credibility on willingness to accept a review. Previously, Levin and Cross (2004) showed that credibility mediates strong-ties through receipt of knowledge, but this credibility mediation is not observed for weak-ties, where a direct path to it is activated. Thus, the predictive power of credibility on behavioral intention - that is, willingness to accept a review - is expected to be higher for strong-ties.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.372-377
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• 2007

다양한 상품의 거래와 다양한 거래방식의 등장으로 인하여 온라인상에서 신뢰의 문제는 매우 큰 관심이 되고 있다. 이에 본 연구에서는 오픈마켓의 구매의견 내용의 분석을 통해 현재 운영중인 피드백 시스템이 신뢰구축과 관련된 요인들을 적절히 반영하고 있는지 살펴보았다. 총 2000건의 구매의견 내용의 분석 결과 항목별 가중치의 부여와 제품속성을 반영한 항목 구성이 필요할 것으로 본다.

• Distribution Business Review
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• no.3
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• pp.41-53
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• 2003

본 연구는 대형 유통상업시절에 멀티플렉스 영화관등 잡객시절을 복합개발에 따른 효과를 분석하는데 중점을 두었다. 국내외 문헌연구자료와 실제 사례시절 고객조사를 통한 실증분석을 하여 잡객시절의 효과를 규명함으로서 복합유통상업시절의 개발전략에 적용할 수 있는 전략요인들을 파악하였다. 향후 복합유통상업시절을 개발하는 경우 상권특성을 물론 개발시절의 목표객층과 상품특성 등을 면밀하게 분석하여 잡객시절의 복합여부 및 적절한 시설선택이 이루어져야 할 것이다.

• Annual Conference on Human and Language Technology
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• 2008.10a
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• pp.183-188
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• 2008

본 연구에서는 문서 안에 있는 문장들 중 비교 문장을 추출해낸다. 비교 문장이란 두 개 이상의 객체, 혹은 한 객체의 시간차, 공간차 등에 따른 변화를 비교하는 내용을 포함하는 문장을 말한다. 비교 문장을 구별해내는 작업은 많은 분야에서 응용될 수 있는데, 특히 객체(사람, 상품 등)에 대한 평가 면에서 매우 직접적이고 확실한 자료로 활용될 수 있다. 비교문장 추출을 위해 본 연구에서는 비교어휘를 이용한 추출 및 MEM(Maximum Entropy Model)을 적용하였으며, 뉴스기사(news article), 상품에 대한 고객리뷰(customer review) 등의 문서를 대상으로 실험하여 재현율 88.40%, 정확률 88.68%의 결과를 산출하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7485-7493
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• 2015

With the popularity of Korean Wave, making cultural goods specific for Hallyu tourists is getting more important. However, there are mainly daily life goods using celebrity character-based ones. Remarkably, there are only a few cultural goods especially in practicality-based clothing category. In particular, few cultural goods related to children's wear have been developed. Therefore, if children's wear is developed as Korean Wave cultural goods considering Chinese consumers' pattern and Korean Wave cultural goods, it will be helpful for revitalizing the Korean Wave and Korea's fashion market. In this regard, the purpose of this study is to develop children's wear design as Korean Wave cultural goods, thereby presenting empirical research results and fulfilling its following objectives: First, it is to identify the concept of Korean Wave cultural goods, to analyze the current status to finally establish data to develop Korean Wave cultural goods needed at this time. Second, it is to make real-life size works through development of designs to provide the empirical data for Korean Wave cultural goods market. For the research method and contents the review of the previous research, in-depth interview for qualitative research, and empirical research using market research and development of work were performed. Through the final research outcomes, Korean Wave cultural goods, the children's wear that can meet the consumer's needs were presented as empirical data. The study can be used as basic data for domestic fashion market and cultural product market and it is meaningful as a reference for the analysis on the Chinese consumers' needs.

• The Journal of Society for e-Business Studies
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• v.15 no.1
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• pp.39-60
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• 2010

It becomes common thing that many customers buy the goods through the online shopping mall as internet grows very fast. The information cascades that happen when a person imitates the other's acts also it occurs in online. Many people buy the goods referring on other people's purchasing experiences and such cases are spreading more and more. Through numerous existing researches, the researches in association with this issue have been studied on the information cascades effect on offline or online separately. The research of comparing the information cascades effects from the offline word of mouth (WOM) and the online review has not studied yet. On that reason this study shows that the online review induces the information cascades. We also compared the effects with information cascades effects from traditional offline word of mouth. In result of this study, the following points have been concluded. Firstly, we examined that information cascades was occurred through both the online review and offline word of mouth. Secondly, the information cascades effect through the online review is greater than through the offline words of mouth. It means the company has to understand the importance of the online review and manage it. Thirdly, the information cascades effects are occurred differently in accordance with the goods brands. Therefore a company has to know whether its products is superior to the competitor's one or not.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.693-700
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• 2023

Sentiment analysis, a branch of natural language processing that classifies and identifies subjective opinions and emotions in text documents as positive or negative, can be used for various promotions and services through customer preference analysis. To this end, recent research has been conducted utilizing various techniques in machine learning and deep learning. In this study, we propose an optimal language model by comparing the accuracy of sentiment analysis for movie, product, and game reviews using existing RNN-based models and recent Transformer-based language models. In our experiments, LMKorBERT and GPT3 showed relatively good accuracy among the models pre-trained on the Korean corpus.