• 한국벤처창업학회:학술대회논문집
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• 한국벤처창업학회 2022년도 춘계학술대회
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• pp.123-126
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• 2022

Online reviews offer valuable information to businesses by reflecting consumer experiences about their products and services. Two important aspects of online reviews are first, the topics consumers choose to address and second, the sentiments expressed in their reviews. Building upon previous literature that shows online reviews are context-dependent, we examine the impact of topic distribution on review sentiment in South Korea and the U.S. during pre-and post-pandemic periods. After performing topic modeling on Airbnb app review data, we measure the contribution of each topic on review sentiment using SHAP values. Our results indicate variations in topic distribution trends between 2018 and 2021. Also, the order and magnitude of topics' impact on review sentiment change between pre-and post-pandemic periods for both countries. This study can help businesses to understand how topics and sentiments associated with their products and services changed after pandemic, and also help them identify areas of improvement.

• Asia pacific journal of information systems
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• 제32권3호
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• pp.514-536
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• 2022

Online reviews offer valuable information to businesses by reflecting consumer experiences about their products and services. Two crucial aspects of online reviews are the topics consumers choose to address, and the sentiments expressed in their reviews. Building upon previous literature that shows online reviews are context-dependent, we employ the Expectation-Confirmation Theory (ECT) to examine the impact of topic distribution on review sentiment in South Korea and the U.S. during pre- and post-pandemic periods. After applying a topic modeling to Airbnb app review data, we measure the contribution of each topic on review sentiment using SHAP values. Our results indicate variations in topic distribution trends between 2018 and 2021. In addition, the order and magnitude of topics' impact on review sentiment change between pre- and post-pandemic periods for both countries. This study can help businesses understand how topics and sentiments associated with their products and services changed after the pandemic and thus identify areas of improvement.

• 한국컴퓨터정보학회논문지
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• 제25권6호
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• pp.81-89
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• 2020

우리가 SNS상에서 흔하게 접하는 온라인 리뷰에는, 소비자들의 선호도에 영향을 미치는 다양한 평가정보가 복합적으로 포함되어 있지만 이를 매우 간단한 형태의 수치(또는 평점)로 제공하는 것이 일반적이다. 이러한 리뷰에서, 소비자가 원하는 구체적인 정보를 얻고, 이를 구매를 위한 판단에 활용하기란 쉽지 않다. 따라서 본 연구에서는 한국어로 작성된 음식점 리뷰를 대상으로, 감성분석을 수행하여 평가항목별로 세분화된 평점을 제공 가능한 예측 방법론을 제안한다. 이를 위해, 음식점의 주요 평가항목으로 '음식', '가격', '서비스', '분위기'를 선정하고, 평가항목별 맞춤형 감성사전을 새롭게 구축한다. 또한 평가항목별 리뷰 문장을 분류하고 감성분석을 통해 세분화된 평점을 예측하여 소비자가 의사결정에 활용 가능한 추가적인 정보를 제공한다. 마지막으로, MAE와 RMSE를 평가지표로 사용하여 기존의 연구보다 제안기법의 평점 예측 정확도가 향상되었음을 보이며, 제안 방법론의 활용 사례도 제시한다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2022년도 제66차 하계학술대회논문집 30권2호
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• pp.697-699
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• 2022

Based on the integrated analysis of the existing literature, this study combined with S-O-R model to explore the impact of e-commerce live broadcast characteristics on consumers' impulse purchase intention. Among them, interactive, entertaining, economical and visual features are selected as the features of e-commerce live broadcast; Select pleasure and arousal to measure consumer sentiment, and build a theoretical model among e-commerce live broadcast features, consumer sentiment and consumers' impulsive purchase intention to specifically explore the impact of each feature on emotion and the further impact of emotion on impulsive purchase intention.

• 복식문화연구
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• 제32권1호
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• pp.38-57
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• 2024

This study utilizes social big data to investigate the factors influencing the awareness, attitude, and behavior toward vegan fashion consumption among global and Korean consumers. Social media posts containing the keyword "vegan fashion" were gathered, and meaningful discourse patterns were identified using semantic network analysis and sentiment analysis. The study revealed that diverse factors guide the purchase of vegan fashion products within global consumer groups, while among Korean consumers, the predominant discourse involved the concepts of veganism and ethics, indicating a heightened awareness of vegan fashion. The research then delved into the factors underpinning awareness (comprehension of animal exploitation, environmental concerns, and alternative materials), attitudes (both positive and negative), and behaviors (exploration, rejection, advocacy, purchase decisions, recommendations, utilization, and disposal). Global consumers placed great significance on product-related information, whereas Korean consumers prioritized ethical integrity and reasonable pricing. In addition, environmental issues stemming from synthetic fibers emerged as a significant factor influencing the awareness, attitude, and behavior regarding vegan fashion consumption. Further, this study confirmed the potential presence of cultural disparities influencing overall awareness, attitude, and behavior concerning the acceptance of vegan fashion, and offers insights into vegan fashion marketing strategies tailored to specific cultures, aiming to provide vegan fashion companies and brands with a deeper understanding of their consumer base.

• 응용통계연구
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• 제24권5호
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• pp.745-758
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• 2011

An Economic Sentiment Indicator(ESI) is a composite indicator of business survey indices(BSI) and consumer survey indices(CSI). The ESI designed to reflect economic agents' (this includes producers and consumers) overall perceptions of economic activity in a one-dimensional index. The European Commission has published an ESI since 1985. This paper demonstrates the construction of an ESI for the Korean economy. The BSI and CSI components (having a high correlation and a leading feature with respect to GDP) are selected to construct the ESI and they are aggregated using a weighted average and then scaled to have a long-term average of 100 and a standard deviation of 10. Thus values greater than 100 indicate an above-average economic sentiment and vice versa. The newly constructed Korean ESI that extends to January 2003 shows a good tracking performance of GDP and adequately reflects the overall perception of economic activity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.5905-5926
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• 2017

Sentiments can profoundly affect individual behavior as well as decision-making. Confronted with the ever-increasing amount of review information available online, it is desirable to provide an effective sentiment model to both detect and organize the available information to improve understanding, and to present the information in a more constructive way for consumers. This study developed a unified phrase-based topic and sentiment detection model, combined with a tracking model using incremental hierarchical dirichlet allocation (PTSM_IHDP). This model was proposed to discover the evolutionary trend of topic-based sentiments from online reviews. PTSM_IHDP model firstly assumed that each review document has been composed by a series of independent phrases, which can be represented as both topic information and sentiment information. PTSM_IHDP model secondly depended on an improved time-dependency non-parametric Bayesian model, integrating incremental hierarchical dirichlet allocation, to estimate the optimal number of topics by incrementally building an up-to-date model. To evaluate the effectiveness of our model, we tested our model on a collected dataset, and compared the result with the predictions of traditional models. The results demonstrate the effectiveness and advantages of our model compared to several state-of-the-art methods.

• 한국산학기술학회논문지
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• 제17권11호
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• pp.474-482
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• 2016

본고에서는 소비자들이 느끼는 체감경기가 경제성장률 등 통상적인 거시경제지표와 괴리될 수 있으며, 특히 소득, 연령, 종사상의 지위 등 각 소비자들의 특성에 따라 차이가 난다는 점에 주목하여 소비자의 체감경기에 영향을 미치는 요인이 무엇인지 살펴보았다. 소비자들의 체감경기를 나타내는 변수로는 한국은행의 소비자동향조사를 통해 파악되는 현재생활 형편 소비자심리지수(CSI)를 사용하였으며 전반적인 실물경기 상황을 나타내는 지표로는 국내총생산(계절조정) 전기대비 증가율을 이용하였다. 이 외에 개별 소비자들의 체감경기에 영향을 미치는 요인으로 임금, 구인배율, 주택매매가격, 주가지수, 생활물가지수, 가계부채상환부담 등을 고려하였는데 분석결과 상기한 거시경제지표들이 소비자들의 체감경기에 상당한 영향을 미치는 것으로 확인되었다. 특히 소득, 연령, 종사상의 지위 등 소비자의 특성별로 그룹을 나누어 분석하여 본 결과, 상기한 거시경제지표들이 체감경기에 영향을 미치는 정도는 소비자 그룹별로 차이가 있는 것으로 확인되었다. 또한 소비자들이 느끼는 체감경기가 경제성장률로 대표되는 실물경기 지표와 크게 괴리되었던 과거의 경우에도 임금, 구인배율 등 상기한 거시경제지표들을 추가적으로 고려하면 이러한 괴리의 상당 부분을 설명할 수 있음을 확인할 수 있었다.

• Asia pacific journal of information systems
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• 제29권4호
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• pp.838-855
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• 2019

Online product reviews are a vital source for companies in that they contain consumers' opinions of products. The earlier methods of opinion mining, which involve drawing semantic information from text, have been mostly applied in one dimension. This is not sufficient in itself to elicit reviewers' comprehensive views on products. In this paper, we propose a novel approach in opinion mining by projecting online consumers' reviews in a multidimensional framework to improve review interpretation of products. First of all, we set up a new framework consisting of six dimensions based on a marketing management theory. To calculate the distances of review sentences and each dimension, we embed words in reviews utilizing Google's pre-trained word2vector model. We classified each sentence of the reviews into the respective dimensions of our new framework. After the classification, we measured the sentiment degrees for each sentence. The results were plotted using a radar graph in which the axes are the dimensions of the framework. We tested the strategy on Amazon product reviews of the iPhone and Galaxy smartphone series with a total of around 21,000 sentences. The results showed that the radar graphs visually reflected several issues associated with the products. The proposed method is not for specific product categories. It can be generally applied for opinion mining on reviews of any product category.

• 대한공간정보학회지
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• 제25권2호
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• pp.3-12
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• 2017

위치 기반 서비스를 이용하여 자신이 방문한 장소에 대한 긍정 혹은 부정적 의견을 리뷰로 남기는 것이 일상화되고 있다. 실제 방문자가 작성한 장소 리뷰에 대한 감성분석 결과는 잠재적 소비자뿐 아니라 기업에게도 유용한 정보를 제공할 수 있다. 장소에 대한 감성분석을 실시하기 위해서는 감성분석의 기준이 되는 어휘에 대한 사전이 필요하다. 그러나 현재까지 장소를 표현하는 공간 감성어에 대한 사전이 구축된 바 없다. 이에 본 연구는 실제 방문자가 한국어로 작성한 장소 리뷰 데이터를 분석하여 공간 감성어 사전을 구축하는 방법을 제안하며, 여러 장소 카테고리 중 테마공원을 대상으로 공간 감성어 사전을 구축하였다. 이를 위해 자연어 처리 기법과 통계적 기법을 활용하였으며, 사전에 포함되는 공간 감성어는 감성의 극성에 대한 정보와 극성의 정도에 대한 확률점수를 포함하고 있다. 본 연구에서 구축한 공간 감성어 사전은 3개의 테이블(SSLex_SS, SSLex_single, SSLex_combi)로 구성되며, 총 219개의 어휘를 포함한다. 이를 바탕으로 트위터에서 테마공원에 대해 작성된 글을 대상으로 감성분석을 실시하였으며, 감성의 극성 분류에 대한 전체 정확도가 0.714로 산출됨에 따라 사전의 유효성을 확인할 수 있었다.