• Title/Summary/Keyword: 상호리뷰

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Classical Music Review on Instagram: Accumulating Cultural Capital through Inter-Learning (클래식음악 애호가의 인스타그램 리뷰: 상호 학습을 통한 문화자본 축적)

  • Seong, Yeonju
    • Review of Culture and Economy
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    • v.21 no.2
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    • pp.111-139
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    • 2018
  • This study is about classical music lovers who write a lengthy concert review on instagram. The intention and objective of writing a review is discussed in addition to inter-communication between those reviewers. For the analysis, an interview with 8 reviewers are mainly analyzed with their reviews. As a result, it is found that some affordances of Instagram, easiness, randomness, and friendliness affects them to use Instagram more than other social media. Hence, since Instagram is image-based platform, it helps writers to keep their reviews from getting an attention by other users. Because of their sense of inferiority that they are lacking in classical music knowledge, continuous writing and reading of reviews help them accumulating some amount of cultural capital needed for understanding classical music in a proper way.

A multi-channel CNN based online review helpfulness prediction model (Multi-channel CNN 기반 온라인 리뷰 유용성 예측 모델 개발에 관한 연구)

  • Li, Xinzhe;Yun, Hyorim;Li, Qinglong;Kim, Jaekyeong
    • Journal of Intelligence and Information Systems
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    • v.28 no.2
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    • pp.171-189
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    • 2022
  • Online reviews play an essential role in the consumer's purchasing decision-making process, and thus, providing helpful and reliable reviews is essential to consumers. Previous online review helpfulness prediction studies mainly predicted review helpfulness based on the consistency of text and rating information of online reviews. However, there is a limitation in that representation capacity or review text and rating interaction. We propose a CNN-RHP model that effectively learns the interaction between review text and rating information to improve the limitations of previous studies. Multi-channel CNNs were applied to extract the semantic representation of the review text. We also converted rating into independent high-dimensional embedding vectors representing the same dimension as the text vector. The consistency between the review text and the rating information is learned based on element-wise operations between the review text and the star rating vector. To evaluate the performance of the proposed CNN-RHP model in this study, we used online reviews collected from Amazom.com. Experimental results show that the CNN-RHP model indicates excellent performance compared to several benchmark models. The results of this study can provide practical implications when providing services related to review helpfulness on online e-commerce platforms.

A Study on the Enhancing Recommendation Performance Using the Linguistic Factor of Online Review based on Deep Learning Technique (딥러닝 기반 온라인 리뷰의 언어학적 특성을 활용한 추천 시스템 성능 향상에 관한 연구)

  • Dongsoo Jang;Qinglong Li;Jaekyeong Kim
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.41-63
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    • 2023
  • As the online e-commerce market growing, the need for a recommender system that can provide suitable products or services to customer is emerging. Recently, many studies using the sentiment score of online review have been proposed to improve the limitations of study on recommender systems that utilize only quantitative information. However, this methodology has limitation in extracting specific preference information related to customer within online reviews, making it difficult to improve recommendation performance. To address the limitation of previous studies, this study proposes a novel recommendation methodology that applies deep learning technique and uses various linguistic factors within online reviews to elaborately learn customer preferences. First, the interaction was learned nonlinearly using deep learning technique for the purpose to extract complex interactions between customer and product. And to effectively utilize online review, cognitive contents, affective contents, and linguistic style matching that have an important influence on customer's purchasing decisions among linguistic factors were used. To verify the proposed methodology, an experiment was conducted using online review data in Amazon.com, and the experimental results confirmed the superiority of the proposed model. This study contributed to the theoretical and methodological aspects of recommender system study by proposing a methodology that effectively utilizes characteristics of customer's preferences in online reviews.

Analysis of the Relationship between Service Quality, Satisfaction and Repurchase Intention of On-line Fashion Shopping Malls and the Moderating Effect of Online Reviews (중국 온라인 패션쇼핑몰의 서비스 품질, 만족, 재구매의도간의 관계 및 온라인 리뷰의 조절효과 분석)

  • Jiang, Bao-Zhi;Lee, Young-sook;Lee, Jieun
    • Journal of Internet of Things and Convergence
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    • v.8 no.5
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    • pp.47-54
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    • 2022
  • The development of the Internet of Things led to new services that did not exist before. This required a change to the existing network. This study aims to verify the service quality, satisfaction, repurchase intention relationship, and the moderating effect of online reviews of Chinese consumers using fashion shopping malls. The results of the study showed that from the perspective of consumers in their 20s and 30s in China, the type, reliability, convenience, and interaction of service quality had a positive effect on customer satisfaction and repurchase intention. In addition, negative reviews among online reviews had a great influence on repurchase intention. Based on the results of the study, it will help improve the effect on online product reviews and in-depth understanding of the acceptance of online product reviews for online fashion shopping malls, and establish strategies for fashion companies to effectively manage online product reviews information.

Text Mining Analysis of Customer Reviews on Public Service Robots: With a focus on the Guide Robot Cases (텍스트 마이닝을 활용한 공공기관 서비스 로봇에 대한 사용자 리뷰 분석 : 안내로봇 사례를 중심으로)

  • Hyorim Shin;Junho Choi;Changhoon Oh
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.1
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    • pp.787-797
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    • 2023
  • The use of service robots, particularly guide robots, is becoming increasingly prevalent in public institutions. However, there has been limited research into the interactions between users and guide robots. To explore the customer experience with the guidance robot, we selected 'QI', which has been meeting customers for the longest time, and collected all reviews since the service was launched in public institutions. By using text mining techniques, we identified the main keywords and user experience factors and examined factors that hinder user experience. As a result, the guide robot's functionality, appearance, interaction methods, and role as a cultural commentator and helper were key factors that influenced the user experience. After identifying hindrance factors, we suggested solutions such as improved interaction design, multimodal interface service design, and content development. This study contributes to the understanding of user experience with guide robots and provides practical suggestions for improvement.

Investigating the Factors Influencing the Use of Live Commerce in the Un-tact Era: Focusing on Multidimensional Interactivity, Presence, and Review Credibility (언택트 시대 라이브 커머스 이용 활성화 영향요인 고찰: 다차원적 상호작용성, 현장감, 리뷰 신뢰도를 중심으로)

  • Lee, Ae Ri
    • Knowledge Management Research
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    • v.22 no.1
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    • pp.269-286
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    • 2021
  • As the un-tact and on-tact consumption culture has proliferated due to the impact of COVID-19, 'live commerce', a form of shopping while communicating with customers through real-time streaming broadcasting, is emerging in the commerce and distribution industry. Live commerce provides an environment where customers can get the convenience of online shopping and enjoy un-tact shopping more realistically while communicating with the broadcaster in real time, as if purchasing directly from an offline store. Therefore, purchases using live commerce are expected to increase further. In this study, based on the characteristics of live commerce, the main factors influencing the increase in purchase intention through live commerce were derived and their influences were verified. In particular, this study examined these factors in multiple dimensions with focusing on strong interactivity, realistic presence, and providing detailed reviews with high credibility for products as the features of live commerce. This research collected sample data from actual users of live commerce and empirically analyzed the significance of the factors influencing the purchase increase of live commerce, thereby providing implications for knowledge management in a newly changed commerce environment in the un-tact era.

Impression Formation and Participative Intention in Internet Movie Review Bulletin Board (인터넷 영화 리뷰 게시판에서의 인상형성과 참여의사)

  • Lee, Jeong-Eun;Park, Joo-Yeon
    • 한국HCI학회:학술대회논문집
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    • 2006.02b
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    • pp.721-726
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    • 2006
  • 인터넷 게시판을 통한 커뮤니케이션에서는 상호작용의 결과물이 지속적으로 남아 있어, 상호작용의 당사자뿐 아니라 나중에 참여하는 다른 이용자들의 게시판에 대한 지각에도 영향을 미치게 된다. 따라서 인터넷 게시판에서의 이용자들 간의 상호작용은 게시판의 기술적 형식이나 주제뿐 아니라 게시판에 있는 기존 이용자들의 메시지를 읽고 받은 인상에 따라서도 달라질 수 있다. 본 연구에서는 게시판의 익명성과 메시지의 전문성을 독립변인으로 한 $2{\times}2$ 실험설계에 따라 가상적 CMC 상황에서 피험자들이 영화 리뷰 게시판의 글을 읽도록 하였다. 게시판 기존 이용자 집단에 대해 받은 인상의 긍정성, 모호성, 전문성, 피험자 자신과의 지각된 유사성 및 해당 게시판에 대한 참여의사를 측정하였다. 결과, 전문성이 높은 메시지를 읽은 피험자들은 게시판의 기존 이용자들이 보다 전문적이라는 인상을 받았으며, 해당 게시판에 참여하고자 하는 의사를 더 많이 표시했다. 또한 기존 이용자들에 대한 인상의 긍정성과 유사성, 참여의사 사이에는 상관관계가 있었다. 이 결과는 인터넷 게시판 이용이 기술적 요인뿐만 아니라 게시판의 기존 이용자 집단에 대한 인상에 따라서도 달라질 수 있음을 시사한다.

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Analysis of Text Mining of Consumer's Personality Implication Words in Review of Used Transaction Application (중고거래 어플리케이션 <당근마켓> 리뷰텍스트에 나타난 소비자의 인성 함축단어 텍스트마이닝 분석)

  • Jung, Yea-Rin;Ju, Young-Ae
    • The Journal of the Korea Contents Association
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    • v.21 no.11
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    • pp.1-10
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    • 2021
  • This study analyzes the use and meaning of consumer personality implication words in the review text of the Used Transaction Application . From of May 2021, the data were collected for the past six months by our Web crawler in Seoul and Gyeonggi Province, and a total of 1368 cases were collected first by random sampling, and finally 570 cases were preprocessed. The results are as follows. First, 48.2% of review texts were related to the personality of consumers even though it was a commercial platform of products. Second, the review text is mainly positive, which formed a text network structure based on the keyword 'gratitude'. Third, the review text, which implies consumer character, was divided into two groups: 'extrovert personality' and 'introvert personality' of consumers. And the individuality of the two groups worked together on the platform. In conclusion, we would like to suggest that consumer personality plays an important role in the platform transaction process, that consumer personality will play a role in the services of the platform in the future, and that consumer personality should be studied from various perspectives.

Reciprocal Peer Review and Revision in Writing (동료 간 상호리뷰와 글 수정행동)

  • Jeong, Hei-Sawn;Cho, Kwang-Su;Lee, Nam-Seok;Han, In-Sook;Lee, Jeong-Hee
    • Korean Journal of Cognitive Science
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    • v.23 no.1
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    • pp.47-71
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    • 2012
  • This study examined how students revised their writing after reciprocal peer review and how their revision activities were influenced by the review. Undergraduates in physics class wrote a laboratory reports, exchanged comments with peers, and revised their reports afterward based on the comments they received from their peers. The comparison between the original and the revised drafts showed that students were mainly concerned with micro-meaning revisions, focusing on making changes on individual words, clauses, and sentences. Revisions that dealt with macro-meaning of the texts were not as frequent. Giving and receiving comments influenced later revision activities. Receiving comments on micro-meaning of the texts led to a significant increase in both micro- and macro-meaning revisions. Receiving comments on macro-meaning of the texts, however, did not prompt relevant revision activities. Even when students engaged in macro revision, it was negatively related to writing performance gains in one subgroup, suggesting that even after peers point out macro-problems in their writing, students are not competent to solve the problems yet. The results of the study suggest that more efforts are needed to help them to understand and manipulate the macro-meaning structure of the texts.

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