{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T15:44:15Z","timestamp":1772207055738,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T00:00:00Z","timestamp":1640131200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012456","name":"National Social Science Fund of China","doi-asserted-by":"publisher","award":["18BGL202"],"award-info":[{"award-number":["18BGL202"]}],"id":[{"id":"10.13039\/501100012456","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Beijing Municipal Philosophy and Social Science Foundation","award":["19GLB036"],"award-info":[{"award-number":["19GLB036"]}]},{"name":"National Key Technology R&amp;D Program of China","award":["2019YFC1605306"],"award-info":[{"award-number":["2019YFC1605306"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61877002"],"award-info":[{"award-number":["61877002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Research and Innovation Project of China University of Political Science and Law","award":["10820363"],"award-info":[{"award-number":["10820363"]}]},{"name":"Open Research Fund of Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University","award":["BTBD-2021KF05"],"award-info":[{"award-number":["BTBD-2021KF05"]}]},{"name":"the University of Macau","award":["MYRG2019-00006-FST"],"award-info":[{"award-number":["MYRG2019-00006-FST"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JTAER"],"abstract":"<jats:p>E-commerce has developed greatly in recent years, as such, its regulations have become one of the most important research areas in order to implement a sustainable market. The analysis of a large amount of reviews data generated in the shopping process can be used to facilitate regulation: since the review data is short text and it is easy to extract the features through deep learning methods. Through these features, the sentiment analysis of the review data can be carried out to obtain the users\u2019 emotional tendency for a specific product. Regulators can formulate reasonable regulation strategies based on the analysis results. However, the data has many issues such as poor reliability and easy tampering at present, which greatly affects the outcome and can lead regulators to make some unreasonable regulatory decisions according to these results. Blockchain provides the possibility of solving these problems due to its trustfulness, transparency and unmodifiable features. Based on these, the blockchain can be applied for data storage, and the Long short-term memory (LSTM) network can be employed to mine reviews data for emotional tendencies analysis. In order to improve the accuracy of the results, we designed a method to make LSTM better understand text data such as reviews containing idioms. In order to prove the effectiveness of the proposed method, different experiments were used for verification, with all results showing that the proposed method can achieve a good outcome in the sentiment analysis leading to regulators making better decisions.<\/jats:p>","DOI":"10.3390\/jtaer17010001","type":"journal-article","created":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T02:01:19Z","timestamp":1640224879000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Sentiment Analysis of Review Data Using Blockchain and LSTM to Improve Regulation for a Sustainable Market"],"prefix":"10.3390","volume":"17","author":[{"given":"Zhihua","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Law, China University of Political Science and Law, Beijing 102249, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhihao","family":"Hao","sequence":"additional","affiliation":[{"name":"School of Law, China University of Political Science and Law, Beijing 102249, China"},{"name":"Department of Computer and Information Science, University of Macau, Macau 999078, China"},{"name":"Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer, Beijing Technology and Business University, Beijing 100048, China"},{"name":"National Engineering Laboratory for Agri-Product Quality Traceability, Beijing Technology and Business University, Beijing 100048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6391-6257","authenticated-orcid":false,"given":"Guancheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Science, University of Macau, Macau 999078, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dianhui","family":"Mao","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer, Beijing Technology and Business University, Beijing 100048, China"},{"name":"National Engineering Laboratory for Agri-Product Quality Traceability, Beijing Technology and Business University, Beijing 100048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2497-9519","authenticated-orcid":false,"given":"Bob","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Science, University of Macau, Macau 999078, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Zuo","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer, Beijing Technology and Business University, Beijing 100048, China"},{"name":"National Engineering Laboratory for Agri-Product Quality Traceability, Beijing Technology and Business University, Beijing 100048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jerome","family":"Yen","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Science, University of Macau, Macau 999078, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangjian","family":"Tu","sequence":"additional","affiliation":[{"name":"School of Law, University of Macau, Macau 999078, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4335","DOI":"10.1007\/s10462-019-09794-5","article-title":"Sentiment analysis using deep learning architectures: A review","volume":"53","author":"Yadav","year":"2020","journal-title":"Artif. 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