{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T15:54:56Z","timestamp":1775145296993,"version":"3.50.1"},"reference-count":35,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the sub-project of the National Key R&amp;D Program, Dark Web Intelligence Analysis and User Identification Technology","award":["2017YFC0820702-3"],"award-info":[{"award-number":["2017YFC0820702-3"]}]},{"name":"the sub-project of the National Key R&amp;D Program, Dark Web Intelligence Analysis and User Identification Technology","award":["ZDI135-96"],"award-info":[{"award-number":["ZDI135-96"]}]},{"name":"the National Language Commission key Project, Cross-Media Multilingual Public Opinion Information Processing Based on Big Data in Cyberspace","award":["2017YFC0820702-3"],"award-info":[{"award-number":["2017YFC0820702-3"]}]},{"name":"the National Language Commission key Project, Cross-Media Multilingual Public Opinion Information Processing Based on Big Data in Cyberspace","award":["ZDI135-96"],"award-info":[{"award-number":["ZDI135-96"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Sentiment analysis is the processing of textual data and giving positive or negative opinions to sentences. In the ABSA dataset, most sentences contain one aspect of sentiment polarity, or sentences of one aspect have multiple identical sentiment polarities, which weakens the sentiment polarity of the ABSA dataset. Therefore, this paper uses the SemEval 14 Restaurant Review dataset, in which each document is symmetrically divided into individual sentences, and two versions of the datasets ATSA and ACSA are created. ATSA: Aspect Term Sentiment Analysis Dataset. ACSA: Aspect Category Sentiment Analysis Dataset. In order to symmetrically simulate the complex relationship between aspect contexts and accurately extract the polarity of emotional features, this paper combines the latest development trend of NLP, combines capsule network and BRET, and proposes the baseline model CapsNet-BERT. The experimental results verify the effectiveness of the model.<\/jats:p>","DOI":"10.3390\/sym14051072","type":"journal-article","created":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T05:12:27Z","timestamp":1653455547000},"page":"1072","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Research on Aspect-Level Sentiment Analysis Based on Text Comments"],"prefix":"10.3390","volume":"14","author":[{"given":"Jing","family":"Tian","sequence":"first","affiliation":[{"name":"Xinjiang Multilingual Information Technology Laboratory, Xinjiang Multilingual Information Technology Research Center, College of Software, Xinjiang University, Urumqi 830017, China"}]},{"given":"Wushour","family":"Slamu","sequence":"additional","affiliation":[{"name":"Xinjiang Multilingual Information Technology Laboratory, Xinjiang Multilingual Information Technology Research Center, College of Information Science and Engineering, Xinjiang University, Urumqi 830017, China"}]},{"given":"Miaomiao","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Xinjiang University, Urumqi 830017, China"}]},{"given":"Chunbo","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Xinjiang University, Urumqi 830017, China"}]},{"given":"Xue","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Software, Xinjiang University, Urumqi 830017, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,23]]},"reference":[{"key":"ref_1","first-page":"79","article-title":"Aspect-based sentiment analysis methods in recent years","volume":"7","author":"Madhoushi","year":"2019","journal-title":"Asia-Pac. 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