{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T12:59:29Z","timestamp":1740142769257,"version":"3.37.3"},"reference-count":31,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2022,6,4]],"date-time":"2022-06-04T00:00:00Z","timestamp":1654300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Science and Technology Research Project of Chongqing Municipal Education Commission","award":["KJZD-K202001101"],"award-info":[{"award-number":["KJZD-K202001101"]}]},{"name":"Humanities and Social Sciences Research Project of Chongqing Municipal Education Commission","award":["20SKGH166"],"award-info":[{"award-number":["20SKGH166"]}]},{"name":"Graduate Innovation Fund of Chongqing University of Technology","award":["clgycx20202091"],"award-info":[{"award-number":["clgycx20202091"]}]},{"name":"Chongqing Ba-nan District Science and Technology Bureau Science and Technology Talents Special Project","award":["2020.58"],"award-info":[{"award-number":["2020.58"]}]},{"name":"General Project of Chongqing Natural Science Foundation","award":["cstc2021jcyj-msxmX0162"],"award-info":[{"award-number":["cstc2021jcyj-msxmX0162"]}]},{"name":"National Education Examination Research Project","award":["GJK2021028"],"award-info":[{"award-number":["GJK2021028"]}]},{"DOI":"10.13039\/501100011786","name":"Chongqing Municipal Human Resources and Social Security Bureau","doi-asserted-by":"publisher","award":["cx2020031"],"award-info":[{"award-number":["cx2020031"]}],"id":[{"id":"10.13039\/501100011786","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Party Construction Project of Chongqing University of Technology","award":["DJ20190306"],"award-info":[{"award-number":["DJ20190306"]}]},{"name":"National Statistical Science Research Project","award":["2020412"],"award-info":[{"award-number":["2020412"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Target-specific sentiment analysis is an emerging topic in the field of text mining but current approaches to deriving the polarity of a sentence suffer from two main drawbacks: on one hand, we lack of a large and well-curated corpus, and on the other hand, current solutions based on deep learning are particularly vulnerable to the attack of adversarial samples. A novel target-specific sentiment classification method is proposed. Firstly, the method of masking target entities is applied to replace synonyms and insert words randomly; secondly, the target-specific sentiment classification model of adversarial learning is constructed with six baseline models; finally, we combine data enhancement and adversarial learning to construct target-specific sentiment classification model. Experimental results show that Macro-F1 values are improved by 0.30\u20132.91, 0.88\u20132.42 and 0.13\u20131.94% compared to the six baseline models by using Laptop14, Restaurant14 and Twitter original datasets, respectively, using Adversarial learning. Using word-masking data enhancement samples and Adversarial learning from Laptop14, Restaurant14 and Twitter shows that Macro-F1 values are improved by 0.9\u20132.64, 1.59\u20133.09 and 0.18\u20131.71% compared to the six baseline (SC), respectively. Our method can effectively improve the quality of samples, it improves the classification performance and the capability of adversarial samples defense.<\/jats:p>","DOI":"10.1093\/comjnl\/bxac066","type":"journal-article","created":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T19:16:21Z","timestamp":1652210181000},"page":"2138-2154","source":"Crossref","is-referenced-by-count":1,"title":["Target-specific sentiment analysis method combining word-masking data enhancement and adversarial learning"],"prefix":"10.1093","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8619-0356","authenticated-orcid":false,"given":"Xiaoyang","family":"Liu","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Chongqing University of Technology, Banan District , No. 69 Red Road, Chongqing 400054 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5681-9520","authenticated-orcid":false,"given":"Shanghong","family":"Dai","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Chongqing University of Technology, Banan District , No. 69 Red Road, Chongqing 400054 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1528-7203","authenticated-orcid":false,"given":"Giacomo","family":"Fiumara","sequence":"additional","affiliation":[{"name":"MIFT Department, University of Messina , V.le F. 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