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NTIS 바로가기지능정보연구 = Journal of intelligence and information systems, v.29 no.4, 2023년, pp.325 - 345
체르냐예바 올가 (부산대학교 경영학부) , 홍태호 (부산대학교 경영학부)
In the rapidly evolving domain of e-commerce, our study presents a cohesive approach to enhance customer satisfaction prediction from online reviews, aligning methodological innovation with practical insights. We integrate the RFE-SHAP feature selection with LDA topic modeling to streamline predicti...
Aakash, A., & Gupta Aggarwal, A. (2022). Assessment?of hotel performance and guest satisfaction?through eWOM: big data for better insights.?International Journal of Hospitality & Tourism?Administration, 23(2), 317-346.
Alzahrani, S., Wang, Q., & Rana, O. (2022). Latent?Dirichlet Allocation for Customer Satisfaction?Analysis in Online Reviews. Journal of E-Commerce?Research, 16(2), 145-158.
Ansari, G., Gupta, S., & Singhal, N. (2020). Natural?Language Processing in Online Reviews. Journal?of E-commerce and Digital Marketing, 8(1),?34-47.
Bauer, J., & Jannach, D. (2021). Improved Customer?Lifetime Value Prediction With Sequence-To-Sequence Learning and Feature-Based Models.?Journal of E-commerce Research, 21(3), 45-60.
Chen, J., Yuan, S., Lv, D., & Xiang, Y. (2021). A?novel self-learning feature selection approach?based on feature attributions. Expert Systems?with Applications, 183, 115219.
Chen, Y., & Xie, J. (2008). Online customer?review: Word-of-mouth as a new element of?marketing communication mix. Management?science, 54(3), 477-491.
Cui, G., Lui, H. K., & Guo, X. (2012). The effect of?online customer reviews on new product sales.?International Journal of Electronic Commerce,?17(1), 39-58.
Darko, A. P., & Liang, D. (2022). Modeling?customer satisfaction through online reviews:?A FlowSort group decision model under?probabilistic linguistic settings. Expert Systems?with Applications, 195, 116649.
Darst, B. F., Malecki, K. C., & Engelman, C. D.?(2018). Using recursive feature elimination in?random forest to account for correlated variables?in high dimensional data. BMC genetics, 19(1),?1-6.
Ding, X., Yang, F., & Ma, F. (2022). An efficient?model selection for linear discriminant function-based recursive feature elimination. Journal of?Biomedical Informatics, 129, 104070.
Du, C., & Huang, L. (2018). Text classification?research with attention-based recurrent neural?networks. International Journal of Computers?Communications & Control, 13(1), 50-61.
Engler, T. H., Winter, P., & Schulz, M. (2015).?Understanding online product ratings: A customer?satisfaction model. Journal of Retailing and?Customer Services, 27, 113-120.
Guo, J., Wang, Z., Jin, Y., Li, M., & Chen, Q.?(2023). Predicting and extracting thermal?behavior rules of hydronic thermal barrier?with interpretable ensemble learning in the?heating season. Energy and Buildings, 113699.
He, J., Hu, D., Zhang, W., & Liu, T. (2020).?Probabilistic Topic Modeling for Sentiment?Analysis of Online Reviews. Journal of Business?Analytics, 7(3), 210-227.
Herrera, G. P., Constantino, M., Su, J. J., &?Naranpanawa, A. (2023). The use of ICTs?and income distribution in Brazil: A machine?learning explanation using SHAP values.?Telecommunications Policy, 47(8), 102598.
Hong, A. C. Y., Khaw, K. W., Chew, X., & Yeong,?W. C. (2023). Prediction of US airline passenger?satisfaction using machine learning algorithms.?Data Analytics and Applied Mathematics?(DAAM), 8-24.
Jing, H., Yang, P., & Lin, H. (2023). A Multilayer?Stacking Method Base on RFE-SHAP Feature?Selection Strategy for Recognition of Driver's?Mental Load and Emotional State. Expert?Systems with Applications, 121729.
Johar, S., & Mubeen, S. (2020). Sentiment analysis?on large scale Amazon product reviews.?IJSRCSE, 8(1), 7-15.
Kang, D., & Park, Y. (2014). based measurement?of customer satisfaction in mobile service:?Sentiment analysis and VIKOR approach. Expert?Systems with Applications, 41(4), 1041-1050.
Kannari, P. R., Chowdary, N. S., & Biradar, R. L.?(2022). An anomaly-based intrusion detection system using recursive feature elimination?technique for improved attack detection.?Theoretical Computer Science, 931, 56-64.
Karim, A., & Das, R. (2018). Rule-based vs.?Machine Learning: A Comparative Study on?Sentiment Analysis and LDA. International?Journal of Data Science, 5(1), 56-68.
Kumar, S., Yadava, M., & Roy, P. (2019). Fusion?of EEG response and sentiment analysis of?products review to predict customer satisfaction.?Information Fusion, 47, 124-133.
Lin, C. L., Lee, S. H., & Horng, D. J. (2011). The?effects of online reviews on purchasing intention:?The moderating role of need for cognition.?Social Behavior and Personality: an international?journal, 39(1), 71-81.
Liu, B., Zhou, X., Jiang, P., & Zhang, L. (2020).?Customer Satisfaction in B2C E-commerce:?An LDA Approach. E-Commerce Research?and Applications, 14(4), 301-315.
Liu, M., Lu, X., & Song, J. (2016). A New Feature?Selection Method for Text Categorization of?Customer Reviews. E-commerce Research?Letters, 10(1), 5-15.
Maharani, A.P., & Triayudi, A. (2022). Sentiment?Analysis of Indonesian Digital Payment Customer?Satisfaction Towards GOPAY, DANA, and?ShopeePay Using Naive Bayes and K-Nearest?Neighbour Methods. Management and Informatics?Business Journal, 6(1), 1-10.
Matuszelanski, K., & Kopczewska, K. (2022). Customer?Churn in Retail E-Commerce Business: Spatial?and Machine Learning Approach. International?Journal of E-commerce Studies, 15(2), 120-138.
Mudambi, S. M., & Schuff, D. (2010). Research?note: What makes a helpful online review? A?study of customer reviews on Amazon. com.?MIS quarterly, 185-200.
Park, S., & Lee, S.-Y. T. (2023). A Study on the?Relationship between Social Media ESG?Sentiment and Firm Performance. Journal of?Intelligence and Information Systems, 29(3),?317-340.
Park, Y.-J., & Kim, K.-j. (2017). Impact of Semantic?Characteristics on Perceived Helpfulness of?Online Reviews. Journal of Intelligence and?Information Systems, 23(3), 29-44.
Pelegrina, G. D., Duarte, L. T., & Grabisch, M.?(2023). A k-additive Choquet integral-based?approach to approximate the SHAP values for?local interpretability in machine learning.?Artificial Intelligence, 325, 104014.
Ren, Y., Wang, R., & Ji, D. (2016). A?topic-enhanced word embedding for Twitter?sentiment classification. Information Sciences,?369, 188-198.
Ren, Y., Wang, R., & Ji, D. (2016). A?topic-enhanced word embedding for Twitter?sentiment classification. Information Sciences,?369, 188-198.
Samb, M. L., Camara, F., Ndiaye, S., Slimani, Y., &?Esseghir, M. A. (2012). A novel RFE-SVM-based?feature selection approach for classification.?International Journal of Advanced Science?and Technology, 43(1), 27-36.
Uthirapathy, S. E., & Sandanam, D. (2023). Topic?Modelling and Opinion Analysis On Climate?Change Twitter Data Using LDA And BERT?Model. Procedia Computer Science, 218,?908-917.
Van den Broeck, G., Lykov, A., Schleich, M., &?Suciu, D. (2022). On the tractability of SHAP?explanations. Journal of Artificial Intelligence?Research, 74, 851-886.
Wisnu, H., Afif, M., & Ruldevyani, Y. (2020).?Sentiment analysis on customer satisfaction?of digital payment in Indonesia: A comparative?study using KNN and Naive Bayes. Journal of?Physics: Conference Series, 1444(1), 012034.
Xu, H., Li, Z., Chu, C., Chen, Y., Yang, Y., Lu,?H., Wang, H., & Stavrou, A. (2018). Detecting?and Characterizing Web Bot Traffic in a?Large E-commerce Marketplace. International?Journal of E-commerce Research, 16(3), 201-218.
Yu, D., Fang, A., & Xu, Z. (2023). Topic research in?fuzzy domain: Based on LDA topic modelling.?Information Sciences, 648, 119600.
Zhang, J., Ma, X., Zhang, J., Sun, D., Zhou, X., Mi,?C., & Wen, H. (2023). Insights into geospatial?heterogeneity of landslide susceptibility based?on the SHAP-XGBoost model. Journal of?Environmental Management, 332, 117357.
Zhang, M., & Luo, L. (2023). Can customer-posted?photos serve as a leading indicator of restaurant?survival? Evidence from Yelp. Management?Science, 69(1), 25-50.
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