{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T06:52:18Z","timestamp":1760597538552,"version":"3.41.0"},"reference-count":35,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2012,6,1]],"date-time":"2012-06-01T00:00:00Z","timestamp":1338508800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100004963","name":"Seventh Framework Programme","doi-asserted-by":"publisher","award":["257859"],"award-info":[{"award-number":["257859"]}],"id":[{"id":"10.13039\/501100004963","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/J020427\/1"],"award-info":[{"award-number":["EP\/J020427\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Transactions on Asian Language Information Processing"],"published-print":{"date-parts":[[2012,6]]},"abstract":"<jats:p>This article presents two novel approaches for incorporating sentiment prior knowledge into the topic model for weakly supervised sentiment analysis where sentiment labels are considered as topics. One is by modifying the Dirichlet prior for topic-word distribution (LDA-DP), the other is by augmenting the model objective function through adding terms that express preferences on expectations of sentiment labels of the lexicon words using generalized expectation criteria (LDA-GE). We conducted extensive experiments on English movie review data and multi-domain sentiment dataset as well as Chinese product reviews about mobile phones, digital cameras, MP3 players, and monitors. The results show that while both LDA-DP and LDA-GE perform comparably to existing weakly supervised sentiment classification algorithms, they are much simpler and computationally efficient, rendering them more suitable for online and real-time sentiment classification on the Web. We observed that LDA-GE is more effective than LDA-DP, suggesting that it should be preferred when considering employing the topic model for sentiment analysis. Moreover, both models are able to extract highly domain-salient polarity words from text.<\/jats:p>","DOI":"10.1145\/2184436.2184437","type":"journal-article","created":{"date-parts":[[2012,6,11]],"date-time":"2012-06-11T13:03:21Z","timestamp":1339419801000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["Incorporating Sentiment Prior Knowledge for Weakly Supervised Sentiment Analysis"],"prefix":"10.1145","volume":"11","author":[{"given":"Yulan","family":"He","sequence":"first","affiliation":[{"name":"The Open University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2012,6]]},"reference":[{"volume-title":"Proceedings of the Association for Computational Linguistics and the Human Language Technology Conference (ACL-HLT\u201908)","author":"Andreevskaia A.","key":"e_1_2_1_1_1","unstructured":"Andreevskaia , A. and Bergler , S . 2008. When specialists and generalists work together: Overcoming domain dependence in sentiment tagging . In Proceedings of the Association for Computational Linguistics and the Human Language Technology Conference (ACL-HLT\u201908) . 290--298. Andreevskaia, A. and Bergler, S. 2008. When specialists and generalists work together: Overcoming domain dependence in sentiment tagging. In Proceedings of the Association for Computational Linguistics and the Human Language Technology Conference (ACL-HLT\u201908). 290--298."},{"volume-title":"Proceedings of the International Conference on Uncertainty in Artificial Intelligence (UAI\u201909)","author":"Asuncion A.","key":"e_1_2_1_2_1","unstructured":"Asuncion , A. , Welling , M. , Smyth , P. , and Teh , Y. W . 2009. On smoothing and inference for topic models . In Proceedings of the International Conference on Uncertainty in Artificial Intelligence (UAI\u201909) . 27--34. Asuncion, A., Welling, M., Smyth, P., and Teh, Y. W. 2009. On smoothing and inference for topic models. In Proceedings of the International Conference on Uncertainty in Artificial Intelligence (UAI\u201909). 27--34."},{"key":"e_1_2_1_3_1","volume-title":"Proceedings of Advances in Neural Information Processing Systems (NIPS\u201908)","author":"Blei D.","year":"2008","unstructured":"Blei , D. and McAuliffe , J. 2008 . Supervised topic models . In Proceedings of Advances in Neural Information Processing Systems (NIPS\u201908) . 20, 121--128. Blei, D. and McAuliffe, J. 2008. Supervised topic models. In Proceedings of Advances in Neural Information Processing Systems (NIPS\u201908). 20, 121--128."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.5555\/944919.944937"},{"volume-title":"Proceedings of the Association for Computational Linguistics (ACL\u201907)","author":"Blitzer J.","key":"e_1_2_1_5_1","unstructured":"Blitzer , J. , Dredze , M. , and Pereira , F . 2007. Biographies, Bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification . In Proceedings of the Association for Computational Linguistics (ACL\u201907) . 440--447. Blitzer, J., Dredze, M., and Pereira, F. 2007. Biographies, Bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification. In Proceedings of the Association for Computational Linguistics (ACL\u201907). 440--447."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.3115\/1220575.1220620"},{"volume-title":"Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP\u201909)","author":"Dasgupta S.","key":"e_1_2_1_7_1","unstructured":"Dasgupta , S. and Ng , V . 2009. Topic-wise, sentiment-wise, or otherwise? Identifying the hidden dimension for unsupervised text classification . In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP\u201909) . 580--589. Dasgupta, S. and Ng, V. 2009. Topic-wise, sentiment-wise, or otherwise? Identifying the hidden dimension for unsupervised text classification. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP\u201909). 580--589."},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1390334.1390436"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0307752101"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.5555\/1996889.1996918"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.3115\/1220355.1220555"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/asi.v58:12"},{"volume-title":"Proceedings of the Conference on the Advances in Neural Information Processing Systems (NIPS\u201908)","author":"Lacoste-Julien S.","key":"e_1_2_1_13_1","unstructured":"Lacoste-Julien , S. , Sha , F. , and Jordan , M . 2008. DiscLDA: Discriminative learning for dimensionality reduction and classification . In Proceedings of the Conference on the Advances in Neural Information Processing Systems (NIPS\u201908) . Lacoste-Julien, S., Sha, F., and Jordan, M. 2008. DiscLDA: Discriminative learning for dimensionality reduction and classification. In Proceedings of the Conference on the Advances in Neural Information Processing Systems (NIPS\u201908)."},{"key":"e_1_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Li T. Zhang Y. and Sindhwani V. 2009. A non-negative matrix tri-factorization approach to sentiment classification with lexical prior knowledge. In Proceedings of the Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing (ACL-IJCNLP\u201909). 244--252. Li T. Zhang Y. and Sindhwani V. 2009. A non-negative matrix tri-factorization approach to sentiment classification with lexical prior knowledge. 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