{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T17:22:43Z","timestamp":1771003363798,"version":"3.50.1"},"reference-count":33,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2021,9,28]]},"abstract":"<jats:p>Considering the scarcity of Uyghur sentiment resources, in this paper proposed a new combined unsupervised sentiment classification method for Uyghur text without any labeled corpora. In the first part, a Uyghur sentiment dictionary, UYSentiDict, was adopted to classify the sentences. For the sentiment vocabulary matching, both the matching of the original word and the stem were considered, and the influence of sentence patterns, negation words, and degree adverbs were further considered as well. Based on different thresholds, the sentences with higher sentiment values were selected from the lexicon-based classification results as a pseudo-labeled dataset. In the second part, different sentiment characteristics were learned from the pseudo-labeled dataset by the machine learning classifier, and the remaining categorical data were further classified. It can be concluded that the method proposed in this paper has good classification efficiency in Uyghur sentiment corpora in four different fields, and some results were performed better than the classification results of machine learning classifier. Moreover, this method is not restricted by the field of data and does not need to be marked in advance with good training corpus, and can solve the resource shortage problem in the field of Uyghur sentiment classification effectively.<\/jats:p>","DOI":"10.3233\/jcm-204645","type":"journal-article","created":{"date-parts":[[2020,10,2]],"date-time":"2020-10-02T13:59:03Z","timestamp":1601647143000},"page":"829-851","source":"Crossref","is-referenced-by-count":0,"title":["A mixed approach of statistical weighting method and unsupervised method to improve Uyghur sentiment classification"],"prefix":"10.1177","volume":"21","author":[{"given":"Erpan","family":"Yalkun","sequence":"first","affiliation":[{"name":"College of Information Science and Engineering, Xinjiang University, Urumqi, Xinjiang 830046, China"}]},{"given":"Wushour","family":"Slamu","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Xinjiang University, Urumqi, Xinjiang 830046, China"}]},{"given":"Raxida","family":"Turhuntay","sequence":"additional","affiliation":[{"name":"College of Electronic and Information Engineering, Yili Normal University, Yili, Xinjiang 835000, China"}]}],"member":"179","reference":[{"key":"10.3233\/JCM-204645_ref1","doi-asserted-by":"crossref","unstructured":"B. Pang, L. Lee and S. Vaithyanathan, Thumbs up? Sentiment classification using machine learning techniques, in: Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing, 2002, pp. 79\u201386.","DOI":"10.3115\/1118693.1118704"},{"key":"10.3233\/JCM-204645_ref2","doi-asserted-by":"crossref","unstructured":"K. Dave, S. Lawrence and D.M. Pennock, Mining the peanut gallery: Opinion extraction and semantic classification of product reviews, in: International Conference on World Wide Web, 2003, pp. 519\u2013528.","DOI":"10.1145\/775152.775226"},{"key":"10.3233\/JCM-204645_ref3","unstructured":"A.L. Maas, R.E. Daly, P.T. Pham, D. Huang, A.Y. Ng and C. Potts, Learning word vectors for sentiment analysis, in: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, 2011, pp. 142\u2013150."},{"key":"10.3233\/JCM-204645_ref4","unstructured":"A. Esuli and F. Sebastiani, SentiWordNet: A publicly available lexical resource for opinion mining, in: Proceedings of the 5th Conference on Language Resources and Evaluation, 2006, pp. 417\u2013422."},{"key":"10.3233\/JCM-204645_ref5","unstructured":"X. Mou and Y. Du, Sentiment classification of Chinese movie reviews in micro-blog based on context, in: IEEE International Conference on Cloud Computing and Big Data Analysis, 2016, pp. 313\u2013318."},{"key":"10.3233\/JCM-204645_ref6","doi-asserted-by":"crossref","unstructured":"T. Li, Y. Zhang and V. Sindhwani, A non-negative matrix tri-factorization approach to sentiment classification with lexical prior knowledge, in: Proceedings of the 47th Annual Meeting of the Association for Computational Linguistics (ACL 2009) and the 4th International Joint Conference on Natural Language Processing of the AFNLP, 2009, pp. 244\u2013252.","DOI":"10.3115\/1687878.1687914"},{"key":"10.3233\/JCM-204645_ref7","doi-asserted-by":"crossref","unstructured":"P. Melville, W. Gryc and R.D. Lawrence, Sentiment analysis of blogs by combining lexical knowledge with text classification, in: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2009, pp. 1275\u20131284.","DOI":"10.1145\/1557019.1557156"},{"issue":"4","key":"10.3233\/JCM-204645_ref8","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1016\/j.ipm.2010.11.003","article-title":"Self-training from labeled features for sentiment analysis","volume":"47","author":"He","year":"2011","journal-title":"Information Processing & Management"},{"key":"10.3233\/JCM-204645_ref9","doi-asserted-by":"crossref","unstructured":"L. Qiu, W. Zhang, C. Hu and K. Zhao, SELC: a self-supervised model for sentiment classification, in: Proceedings of the 18th ACM Conference on Information and Knowledge Management, 2009, pp. 929\u2013936.","DOI":"10.1145\/1645953.1646072"},{"key":"10.3233\/JCM-204645_ref10","unstructured":"J. Wiebe, Learning subjective adjectives from corpora, in: Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence, 2000, pp. 735\u2013740."},{"key":"10.3233\/JCM-204645_ref11","doi-asserted-by":"crossref","unstructured":"P.D. Turney, Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews, in: Proceedings of the Annual Meeting of the Association for Computational Linguistics, 2002, pp. 417\u2013124.","DOI":"10.3115\/1073083.1073153"},{"key":"10.3233\/JCM-204645_ref12","unstructured":"A. Aue and M. Gamon, Customizing sentiment classifiers to new domains: a case study, in: Proceedings of the Recent Advances in Natural Language Processing (RANLP), Borovets, 2005."},{"key":"10.3233\/JCM-204645_ref13","doi-asserted-by":"crossref","unstructured":"S. Dasgupta and V. Ng, Mine the easy, classify the hard: a semi-supervised approach to automatic sentiment classification, in: Proceedings of the 47th Annual Meeting of the Association for Computational Linguistics (ACL 2009) and the 4th International Joint Conference on Natural Language Processing of the AFNLP, 2009, pp. 701\u2013709.","DOI":"10.3115\/1690219.1690244"},{"key":"10.3233\/JCM-204645_ref14","doi-asserted-by":"crossref","unstructured":"A.B. Goldberg and X. Zhu, Seeing stars when there aren\u2019t many stars: graph-based semi-supervised learning for sentiment categorization, in: Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing, 2006, pp. 45\u201352.","DOI":"10.3115\/1654758.1654769"},{"key":"10.3233\/JCM-204645_ref15","unstructured":"S. Li, C.R. Huang, G. Zhou and S.Y.M. Lee, Employing personal\/impersonal views in supervised and semi-supervised sentiment classification, in: Proceedings of the Annual Meeting of the Association for Computational Linguistics, 2010, pp. 414\u2013423."},{"issue":"1","key":"10.3233\/JCM-204645_ref16","first-page":"61","article-title":"Semi-supervised sentiment classification with social network","volume":"50","author":"Xue","year":"2014","journal-title":"Acta Scientiarum Naturalium Universitatis Pekinensis"},{"issue":"2","key":"10.3233\/JCM-204645_ref17","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1111\/j.1467-8640.2006.00277.x","article-title":"Sentiment classification of movie reviews using contextual valence shifters","volume":"22","author":"Kennedy","year":"2006","journal-title":"Computational Intelligence"},{"issue":"2","key":"10.3233\/JCM-204645_ref18","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1162\/COLI_a_00049","article-title":"Lexicon-based methods for sentiment analysis","volume":"37","author":"Taboada","year":"2011","journal-title":"Computational Linguistics"},{"key":"10.3233\/JCM-204645_ref19","unstructured":"T. Zagibalov and J. Carroll, Unsupervised classification of sentiment and objectivity in Chinese text, in: Proceedings of the Third International Joint Conference on Natural Language Processing, 2008, pp. 304\u2013311."},{"key":"10.3233\/JCM-204645_ref20","unstructured":"A. Andreevskaia and S. Bergler, When specialists and generalists work together: Overcoming domain dependence in sentiment tagging, in: Proceedings of Association for Computational Linguistics-08: HLT, 2008, pp. 290\u2013298."},{"key":"10.3233\/JCM-204645_ref21","doi-asserted-by":"crossref","unstructured":"S. Tan, Y. Wang and X. Cheng, Combining learn-based and lexicon-based techniques for sentiment detection without using labeled examples, in: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2008, pp. 743\u2013744.","DOI":"10.1145\/1390334.1390481"},{"key":"10.3233\/JCM-204645_ref22","doi-asserted-by":"crossref","unstructured":"S. Tan, G. Wu, H. Tang and Z. Cheng, A novel scheme for domain transfer problem in the context of sentiment analysis, in: Proceedings of the CIKM, 2007, pp. 979\u2013982.","DOI":"10.1145\/1321440.1321590"},{"issue":"10","key":"10.3233\/JCM-204645_ref23","first-page":"2371","article-title":"The sentiment classification of Uyghur sentences based on sentiment dictionary","volume":"10","author":"Yusuf","year":"2014","journal-title":"Computer Knowledge and Technology"},{"issue":"9","key":"10.3233\/JCM-204645_ref24","first-page":"183","article-title":"Sentence sentiment analysis based on Uyghur sentiment word","volume":"38","author":"Huang","year":"2012","journal-title":"Computer Engineering"},{"issue":"7","key":"10.3233\/JCM-204645_ref25","first-page":"171","article-title":"Analysis of the sentence tendency in Uighur language","volume":"25","author":"Nian","year":"2016","journal-title":"Computer Systems & Applications"},{"key":"10.3233\/JCM-204645_ref26","unstructured":"M.A. Mageed and M. Diab, Toward building a large-scale Arabic sentiment lexicon, in: Proceedings of the 6th International Global WordNet Conference, 2012, pp. 18\u201322."},{"issue":"4","key":"10.3233\/JCM-204645_ref27","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1016\/j.dss.2012.05.029","article-title":"Creating sentiment dictionaries via triangulation","volume":"53","author":"Steinberger","year":"2012","journal-title":"Decis. Support Syst"},{"key":"10.3233\/JCM-204645_ref28","unstructured":"C. Chen, H. Huang and H. Chen, NTUSD-Fin: A Market Sentiment Dictionary for Financial Social Media Data Applications, in: Proceedings of the First Financial Narrative Processing Workshop, 2018."},{"issue":"4","key":"10.3233\/JCM-204645_ref30","doi-asserted-by":"crossref","first-page":"1049","DOI":"10.1007\/s10579-013-9218-3","article-title":"Bootstrapping polarity classifiers with rule-based classification","volume":"47","author":"Wiegand","year":"2013","journal-title":"Language Resources & Evaluation"},{"key":"10.3233\/JCM-204645_ref33","first-page":"57","article-title":"Classification of chinese texts sentiment based on semantic and conjunction","volume":"52","author":"Liu","year":"2015","journal-title":"Journal of Sichuan University Natural Science Edition"},{"key":"10.3233\/JCM-204645_ref34","first-page":"11","article-title":"An analysis of statements of negation in the modern Uygur language","volume":"2","author":"Li","year":"2001","journal-title":"Language & Translation"},{"issue":"13","key":"10.3233\/JCM-204645_ref36","first-page":"56","article-title":"Feature selection and machine learning algorithms for Uyghur text sentiment classification","volume":"55","author":"Turhuntay","year":"2017","journal-title":"Bolet\u00edn T\u00e9cnico"},{"issue":"8","key":"10.3233\/JCM-204645_ref37","first-page":"80","article-title":"Uyghur text sentiment classification based on bi-tagged features","volume":"32","author":"Turhuntay","year":"2018","journal-title":"Journal of Chinese Information Processing"}],"container-title":["Journal of Computational Methods in Sciences and Engineering"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JCM-204645","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T16:32:01Z","timestamp":1771000321000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JCM-204645"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,28]]},"references-count":33,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.3233\/jcm-204645","relation":{},"ISSN":["1472-7978","1875-8983"],"issn-type":[{"value":"1472-7978","type":"print"},{"value":"1875-8983","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,28]]}}}