{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:33:07Z","timestamp":1750221187323,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":21,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,12,8]],"date-time":"2018-12-08T00:00:00Z","timestamp":1544227200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100011002","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772337,61472248,U1736207"],"award-info":[{"award-number":["61772337,61472248,U1736207"]}],"id":[{"id":"10.13039\/501100011002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2018,12,8]]},"DOI":"10.1145\/3297156.3297189","type":"proceedings-article","created":{"date-parts":[[2019,2,28]],"date-time":"2019-02-28T13:07:04Z","timestamp":1551359224000},"page":"409-413","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Sentiment Analysis of Network Comments Based on GCNN"],"prefix":"10.1145","author":[{"given":"Chen","family":"Huang","sequence":"first","affiliation":[{"name":"Shanghai Jiao Tong University, China"}]},{"given":"Gongshen","family":"Liu","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, China"}]}],"member":"320","published-online":{"date-parts":[[2018,12,8]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.3115\/1073083.1073153"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.3115\/1118693.1118704"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/133160.133172"},{"key":"e_1_3_2_1_4_1","volume-title":"Explicit and implicit syntactic features for text classification","author":"Post M.","year":"2013","unstructured":"Post , M. Bergsma , S. 2013. Explicit and implicit syntactic features for text classification . Association for Computational Linguistics , 2013 :866--872. Post, M. Bergsma, S. 2013. Explicit and implicit syntactic features for text classification. Association for Computational Linguistics, 2013:866--872."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015435"},{"key":"e_1_3_2_1_6_1","volume-title":"Elements of information theory","author":"Cover T. M.","year":"2006","unstructured":"Cover , T. M. Thomas , J. A. 2006. Elements of information theory ( 2 nd ed.).Canada: John W , Sons , 2006 :7--38. Cover, T. M. Thomas, J. A. 2006. Elements of information theory(2nd ed.).Canada: John W, Sons, 2006:7--38.","edition":"2"},{"issue":"3","key":"e_1_3_2_1_7_1","first-page":"90","article-title":"2011. Feature representation based on sentimental orientation classification","volume":"8","author":"Liu G. S.","year":"2011","unstructured":"Liu , G. S. He , W. L. Zhu , J. . 2011. Feature representation based on sentimental orientation classification . China Communications , 2011 , 8 ( 3 ): 90 -- 98 . Liu, G. S. He, W. L. Zhu, J. et al. 2011. Feature representation based on sentimental orientation classification. China Communications, 2011, 8(3): 90--98.","journal-title":"China Communications"},{"key":"e_1_3_2_1_8_1","volume-title":"Proceedings of International Conference on Neural Information Processing Systems","author":"Mikolov T.","year":"2013","unstructured":"Mikolov , T. Sutskever , I. Chen , K. et al. 2013. Distributed representations of words and phrases and their compositionality . Proceedings of International Conference on Neural Information Processing Systems . New York, USA: ACM Press , 2013 , 26: 3111--3119. Mikolov, T. Sutskever, I. Chen, K. et al. 2013. Distributed representations of words and phrases and their compositionality. Proceedings of International Conference on Neural Information Processing Systems. New York, USA: ACM Press, 2013, 26:3111--3119."},{"key":"e_1_3_2_1_9_1","volume-title":"Proceedings of International Conference on Intelligent Text Processing and Computational Linguistics","author":"Mikolov T.","year":"2013","unstructured":"Mikolov , T. Chen , K. Corrado , G. et al. 2013 Efficient Estimation of Word Representations in Vector Space . Proceedings of International Conference on Intelligent Text Processing and Computational Linguistics . Berlin, Germany : Springer, 2013 : 430--443. Mikolov, T. Chen, K. Corrado, G. et al. 2013 Efficient Estimation of Word Representations in Vector Space. Proceedings of International Conference on Intelligent Text Processing and Computational Linguistics. Berlin, Germany: Springer, 2013:430--443."},{"key":"e_1_3_2_1_10_1","volume-title":"Glove: Global Vectors for Word Representation. Conference on Empirical Methods in Natural Language Processing(EMNLP)","author":"Pennington J.","year":"2014","unstructured":"Pennington , J. Socher , R. Manning , C. D. 2014 . Glove: Global Vectors for Word Representation. Conference on Empirical Methods in Natural Language Processing(EMNLP) , 2014: 1532--1543. Pennington, J. Socher, R. Manning, C. D. 2014. Glove: Global Vectors for Word Representation. Conference on Empirical Methods in Natural Language Processing(EMNLP), 2014: 1532--1543."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1181"},{"volume-title":"Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers","author":"Zeng D. J.","key":"e_1_3_2_1_12_1","unstructured":"Zeng , D. J. Liu , K. Lai , S. W. et al. 2014. Relation classification via convolutional deep neural network . In Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers , 2014: 2335--2344. Zeng, D. J. Liu, K. Lai, S. W. et al. 2014. Relation classification via convolutional deep neural network. In Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers, 2014: 2335--2344."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/P14-1062"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1024"},{"volume-title":"proceedings of the 10th International Workshop on Semantic Evaluation(SemEval-2016)","author":"Nakov P.","key":"e_1_3_2_1_15_1","unstructured":"Nakov , P. Ritter , A. Rosenthal , S. et al. 2016. SemEval-2016 Task 4: Sentiment Analysis in Twitter . In proceedings of the 10th International Workshop on Semantic Evaluation(SemEval-2016) . San Diego, California : Association for Computational Linguistics, 2016: 1--18. Nakov, P. Ritter, A. Rosenthal, S. et al. 2016. SemEval-2016 Task 4: Sentiment Analysis in Twitter. In proceedings of the 10th International Workshop on Semantic Evaluation(SemEval-2016). San Diego, California: Association for Computational Linguistics, 2016:1--18."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S15-2079"},{"volume-title":"proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)","author":"Stojanovski D.","key":"e_1_3_2_1_17_1","unstructured":"Stojanovski , D. Strezoski , G. Madjarov , G. et al. 2016. Finki at semeval-2016 task 4: Deep learning architecture for twitter sentiment analysis . In proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016) . San Diego, California : Association for Computational Linguistics, 2016: 149--154. Stojanovski, D. Strezoski, G. Madjarov, G. et al. 2016. Finki at semeval-2016 task 4: Deep learning architecture for twitter sentiment analysis. In proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016). San Diego, California: Association for Computational Linguistics, 2016:149--154."},{"key":"e_1_3_2_1_18_1","volume-title":"Text sentiment analysis based on convolutional neural network combined with part of speech features.Computer Engineering","author":"He H. Y.","year":"2017","unstructured":"He , H. Y. Zhang , J. Zhang , Z. P. 2017. Text sentiment analysis based on convolutional neural network combined with part of speech features.Computer Engineering , 2017 . He, H. Y. Zhang, J. Zhang, Z. P. 2017. Text sentiment analysis based on convolutional neural network combined with part of speech features.Computer Engineering, 2017."},{"key":"e_1_3_2_1_19_1","volume-title":"Application Research of Computers","volume":"35","author":"Hu Z. J.","year":"2018","unstructured":"Hu , Z. J. Zhao , X. W. 2018 . Sentiment analysis based on word vector technology and hybrid neural network . Application Research of Computers , 2018, Vol. 35 No. 12 Hu, Z. J. Zhao, X. W. 2018. Sentiment analysis based on word vector technology and hybrid neural network. Application Research of Computers, 2018, Vol. 35 No. 12"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_21_1","volume-title":"et al","author":"Cho K.","year":"2014","unstructured":"Cho , K. Merrienboer , B. V. Gulcehre , C. et al . 2014 . Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. Eprint Arxiv , 2014. Cho, K. Merrienboer, B. V. Gulcehre, C. et al. 2014. Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. Eprint Arxiv, 2014."}],"event":{"name":"CSAI '18: 2018 2nd International Conference on Computer Science and Artificial Intelligence","sponsor":["Shenzhen University Shenzhen University"],"location":"Shenzhen China","acronym":"CSAI '18"},"container-title":["Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3297156.3297189","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3297156.3297189","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T01:39:09Z","timestamp":1750210749000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3297156.3297189"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12,8]]},"references-count":21,"alternative-id":["10.1145\/3297156.3297189","10.1145\/3297156"],"URL":"https:\/\/doi.org\/10.1145\/3297156.3297189","relation":{},"subject":[],"published":{"date-parts":[[2018,12,8]]},"assertion":[{"value":"2018-12-08","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}