{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T23:38:14Z","timestamp":1776296294349,"version":"3.50.1"},"publisher-location":"New York, New York, USA","reference-count":44,"publisher":"ACM Press","license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"China Scholarship Council"},{"name":"National Science Foundation of China","award":["61272227\/61332007"],"award-info":[{"award-number":["61272227\/61332007"]}]},{"name":"Singapore Ministry of Education Research Fund","award":["MOE2014-T2-2-066"],"award-info":[{"award-number":["MOE2014-T2-2-066"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1145\/3178876.3186015","type":"proceedings-article","created":{"date-parts":[[2018,4,13]],"date-time":"2018-04-13T15:53:48Z","timestamp":1523634828000},"page":"1165-1174","source":"Crossref","is-referenced-by-count":139,"title":["Sentiment Analysis by Capsules"],"prefix":"10.1145","author":[{"given":"Yequan","family":"Wang","sequence":"first","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aixin","family":"Sun","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore , Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jialong","family":"Han","sequence":"additional","affiliation":[{"name":"Tencent AI Lab, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Liu","sequence":"additional","affiliation":[{"name":"Cardiff University, Cardiff, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyan","family":"Zhu","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","reference":[{"key":"key-10.1145\/3178876.3186015-1","unstructured":"Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural Machine Translation by Jointly Learning to Align and Translate. CoRR Vol. abs\/1409.0473 (2014)."},{"key":"key-10.1145\/3178876.3186015-2","unstructured":"Yanqing Chen and Steven Skiena. 2014. Building Sentiment Lexicons for All Major Languages Proc. ACL, Volume 2: Short Papers. 383--389."},{"key":"key-10.1145\/3178876.3186015-3","doi-asserted-by":"crossref","unstructured":"Kyunghyun Cho, Bart van Merrienboer, cCaglar G&#252;lccehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014. Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. In Proc. EMNLP. 1724--1734.","DOI":"10.3115\/v1\/D14-1179"},{"key":"key-10.1145\/3178876.3186015-4","doi-asserted-by":"crossref","unstructured":"Li Dong, Furu Wei, Chuanqi Tan, Duyu Tang, Ming Zhou, and Ke Xu. 2014. Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification. In Proc. ACL, Volume 2: Short Papers. 49--54.","DOI":"10.3115\/v1\/P14-2009"},{"key":"key-10.1145\/3178876.3186015-5","doi-asserted-by":"crossref","unstructured":"Bjarke Felbo, Alan Mislove, Anders S&#248;gaard, Iyad Rahwan, and Sune Lehmann. 2017. Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm. In Proc. EMNLP. 1615--1625.","DOI":"10.18653\/v1\/D17-1169"},{"key":"key-10.1145\/3178876.3186015-6","unstructured":"Andrew B Goldberg and Xiaojin Zhu. 2006. Seeing stars when there aren't many stars: graph-based semi-supervised learning for sentiment categorization. In Proc. Workshop on Graph Based Methods for Natural Language Processing. Association for Computational Linguistics, 45--52."},{"key":"key-10.1145\/3178876.3186015-7","unstructured":"Ian J. Goodfellow, Yoshua Bengio, and Aaron C. Courville. 2016. Deep Learning. MIT Press."},{"key":"key-10.1145\/3178876.3186015-8","unstructured":"Ruidan He, Wee Sun Lee, Hwee Tou Ng, and Daniel Dahlmeier. 2017. An Unsupervised Neural Attention Model for Aspect Extraction Proc. ACL, Volume 1: Long Papers. 388--397."},{"key":"key-10.1145\/3178876.3186015-9","doi-asserted-by":"crossref","unstructured":"Sepp Hochreiter and J&#252;rgen Schmidhuber. 1997. Long Short-Term Memory. Neural Computation Vol. 9, 8 (1997), 1735--1780.","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"key-10.1145\/3178876.3186015-10","unstructured":"Minqing Hu and Bing Liu. 2004. Mining Opinion Features in Customer Reviews. In Proc. National Conference on Artificial Intelligence, Conference on Innovative Applications of Artificial Intelligence. 755--760."},{"key":"key-10.1145\/3178876.3186015-11","doi-asserted-by":"crossref","unstructured":"Mohit Iyyer, Anupam Guha, Snigdha Chaturvedi, Jordan L. Boyd-Graber, and Hal Daum&#233; III. 2016. Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships. In Proc. NAACL HLT. 1534--1544.","DOI":"10.18653\/v1\/N16-1180"},{"key":"key-10.1145\/3178876.3186015-12","unstructured":"Mohit Iyyer, Varun Manjunatha, Jordan L. Boyd-Graber, and Hal Daum&#233; III. 2015. Deep Unordered Composition Rivals Syntactic Methods for Text Classification Proc. ACL, Volume 1: Long Papers. 1681--1691."},{"key":"key-10.1145\/3178876.3186015-13","unstructured":"Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom. 2014. A Convolutional Neural Network for Modelling Sentences Proc. ACL, Volume 1: Long Papers. 655--665."},{"key":"key-10.1145\/3178876.3186015-14","doi-asserted-by":"crossref","unstructured":"Yoon Kim. 2014. Convolutional Neural Networks for Sentence Classification Proc. EMNLP. 1746--1751.","DOI":"10.3115\/v1\/D14-1181"},{"key":"key-10.1145\/3178876.3186015-15","unstructured":"Diederik P. Kingma and Jimmy Ba. 2014. Adam: A Method for Stochastic Optimization. CoRR Vol. abs\/1412.6980 (2014)."},{"key":"key-10.1145\/3178876.3186015-16","doi-asserted-by":"crossref","unstructured":"Dan Klein and Christopher D. Manning. 2003. Accurate Unlexicalized Parsing. In Proc. ACL. 423--430.","DOI":"10.3115\/1075096.1075150"},{"key":"key-10.1145\/3178876.3186015-17","unstructured":"Quoc Le and Tomas Mikolov. 2014. Distributed Representations of Sentences and Documents Proc. ICML. II--1188--II--1196."},{"key":"key-10.1145\/3178876.3186015-18","unstructured":"Tao Lei, Regina Barzilay, and Tommi S. Jaakkola. 2015. Molding CNNs for text: non-linear, non-consecutive convolutions Proc. EMNLP. 1565--1575."},{"key":"key-10.1145\/3178876.3186015-19","doi-asserted-by":"crossref","unstructured":"Tao Lei, Regina Barzilay, and Tommi S. Jaakkola. 2016. Rationalizing Neural Predictions. In Proc. EMNLP. 107--117.","DOI":"10.18653\/v1\/D16-1011"},{"key":"key-10.1145\/3178876.3186015-20","doi-asserted-by":"crossref","unstructured":"Bing Liu. 2012. Sentiment Analysis and Opinion Mining. Morgan &#38; Claypool Publishers.","DOI":"10.1007\/978-3-031-02145-9"},{"key":"key-10.1145\/3178876.3186015-21","unstructured":"Tom&#225;vs Mikolov. 2012. Statistical language models based on neural networks. Presentation at Google, Mountain View, 2nd April (2012)."},{"key":"key-10.1145\/3178876.3186015-22","doi-asserted-by":"crossref","unstructured":"Tomas Mikolov, Martin Karafi&#225;t, Luk&#225;s Burget, Jan Cernock&#253;, and Sanjeev Khudanpur. 2010. Recurrent neural network based language model. In Proc. INTERSPEECH. 1045--1048.","DOI":"10.21437\/Interspeech.2010-343"},{"key":"key-10.1145\/3178876.3186015-23","unstructured":"Tomas Mikolov, Ilya Sutskever, Kai Chen, Gregory S. Corrado, and Jeffrey Dean. 2013. Distributed Representations of Words and Phrases and their Compositionality Proc. NIPS. 3111--3119."},{"key":"key-10.1145\/3178876.3186015-24","unstructured":"Saif Mohammad, Svetlana Kiritchenko, and Xiaodan Zhu. 2013. NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets Proc. Workshop on Semantic Evaluation, SemEval@NAACL-HLT. 321--327."},{"key":"key-10.1145\/3178876.3186015-25","doi-asserted-by":"crossref","unstructured":"Bo Pang and Lillian Lee. 2005. Seeing Stars: Exploiting Class Relationships for Sentiment Categorization with Respect to Rating Scales. In Proc. ACL. 115--124.","DOI":"10.3115\/1219840.1219855"},{"key":"key-10.1145\/3178876.3186015-26","unstructured":"Bo Pang and Lillian Lee. 2007. Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval Vol. 2, 1--2 (2007), 1--135."},{"key":"key-10.1145\/3178876.3186015-27","doi-asserted-by":"crossref","unstructured":"Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014. Glove: Global Vectors for Word Representation. In Proc. EMNLP. 1532--1543.","DOI":"10.3115\/v1\/D14-1162"},{"key":"key-10.1145\/3178876.3186015-28","unstructured":"Qiao Qian, Minlie Huang, JinHao Lei, and Xiaoyan Zhu. 2017. Linguistically Regularized LSTMs for Sentiment Classification Proc. ACL, Vol. Vol. 1. 1679--1689."},{"key":"key-10.1145\/3178876.3186015-29","doi-asserted-by":"crossref","unstructured":"Qiao Qian, Bo Tian, Minlie Huang, Yang Liu, Xuan Zhu, and Xiaoyan Zhu. 2015. Learning Tag Embeddings and Tag-specific Composition Functions in Recursive Neural Network. In Proc. ACL, Volume 1: Long Papers. 1365--1374.","DOI":"10.3115\/v1\/P15-1132"},{"key":"key-10.1145\/3178876.3186015-30","unstructured":"Sara Sabour, Nicholas Frosst, and Geoffrey E. Hinton. 2017. Dynamic Routing Between Capsules. In Proc. NIPS. 3859--3869."},{"key":"key-10.1145\/3178876.3186015-31","unstructured":"Richard Socher, John Bauer, Christopher D. Manning, and Andrew Y. Ng. 2013 a. Parsing with Compositional Vector Grammars. In Proc. ACL, Volume 1: Long Papers. 455--465."},{"key":"key-10.1145\/3178876.3186015-32","unstructured":"Richard Socher, Andrej Karpathy, Quoc V. Le, Christopher D. Manning, and Andrew Y. Ng. 2014. Grounded Compositional Semantics for Finding and Describing Images with Sentences. TACL Vol. 2 (2014), 207--218."},{"key":"key-10.1145\/3178876.3186015-33","unstructured":"Richard Socher, Jeffrey Pennington, Eric H. Huang, Andrew Y. Ng, and Christopher D. Manning. 2011. Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions Proc. EMNLP. 151--161."},{"key":"key-10.1145\/3178876.3186015-34","unstructured":"Richard Socher, Alex Perelygin, Jean Y Wu, Jason Chuang, Christopher D Manning, Andrew Y Ng, and Christopher Potts. 2013 b. Recursive deep models for semantic compositionality over a sentiment treebank Proc. EMNLP, Vol. Vol. 1631. Citeseer, 1642."},{"key":"key-10.1145\/3178876.3186015-35","unstructured":"Kai Sheng Tai, Richard Socher, and Christopher D. Manning. 2015. Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks. In Proc. ACL, Volume 1: Long Papers. 1556--1566."},{"key":"key-10.1145\/3178876.3186015-36","doi-asserted-by":"crossref","unstructured":"Duyu Tang, Bing Qin, and Ting Liu. 2015. Document Modeling with Gated Recurrent Neural Network for Sentiment Classification Proc. EMNLP. 1422--1432.","DOI":"10.18653\/v1\/D15-1167"},{"key":"key-10.1145\/3178876.3186015-37","doi-asserted-by":"crossref","unstructured":"Zhiyang Teng, Duy-Tin Vo, and Yue Zhang. 2016. Context-Sensitive Lexicon Features for Neural Sentiment Analysis Proc. EMNLP. 1629--1638.","DOI":"10.18653\/v1\/D16-1169"},{"key":"key-10.1145\/3178876.3186015-38","doi-asserted-by":"crossref","unstructured":"Peter D. Turney. 2002. Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews. In Proc. ACL. 417--424.","DOI":"10.3115\/1073083.1073153"},{"key":"key-10.1145\/3178876.3186015-39","doi-asserted-by":"crossref","unstructured":"Duy-Tin Vo and Yue Zhang. 2016. Don't Count, Predict! An Automatic Approach to Learning Sentiment Lexicons for Short Text. In Proc. ACL, Volume 2: Short Papers. 219--224.","DOI":"10.18653\/v1\/P16-2036"},{"key":"key-10.1145\/3178876.3186015-40","doi-asserted-by":"crossref","unstructured":"Yequan Wang, Minlie Huang, Li Zhao, and Xiaoyan Zhu. 2016. Attention-based LS&#8482; for Aspect-level Sentiment Classification Proc. EMNLP. 606--615.","DOI":"10.18653\/v1\/D16-1058"},{"key":"key-10.1145\/3178876.3186015-41","doi-asserted-by":"crossref","unstructured":"Wen-Li Wei, Chung-Hsien Wu, and Jen-Chun Lin. 2011. A Regression Approach to Affective Rating of Chinese Words from ANEW Proc. Conference on Affective Computing and Intelligent Interaction, Part II. 121--131.","DOI":"10.1007\/978-3-642-24571-8_13"},{"key":"key-10.1145\/3178876.3186015-42","unstructured":"Jason Weston, Samy Bengio, and Nicolas Usunier. 2011. WSABIE: Scaling Up to Large Vocabulary Image Annotation Proc. IJCAI. 2764--2770."},{"key":"key-10.1145\/3178876.3186015-43","doi-asserted-by":"crossref","unstructured":"Theresa Wilson, Janyce Wiebe, and Paul Hoffmann. 2005. Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis Proc. HLT EMNLP. 347--354.","DOI":"10.3115\/1220575.1220619"},{"key":"key-10.1145\/3178876.3186015-44","doi-asserted-by":"crossref","unstructured":"Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alexander J. Smola, and Eduard H. Hovy. 2016. Hierarchical Attention Networks for Document Classification Proc. NAACL HLT. 1480--1489.","DOI":"10.18653\/v1\/N16-1174"}],"event":{"name":"the 2018 World Wide Web Conference","location":"Lyon, France","acronym":"WWW '18","number":"2018","sponsor":["SIGWEB, ACM Special Interest Group on Hypertext, Hypermedia, and Web","IW3C2, International World Wide Web Conference Committee"],"start":{"date-parts":[[2018,4,23]]},"end":{"date-parts":[[2018,4,27]]}},"container-title":["Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3178876.3186015","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/dl.acm.org\/ft_gateway.cfm?id=3186015&ftid=1957389&dwn=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:26:59Z","timestamp":1750213619000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/citation.cfm?doid=3178876.3186015"}},"subtitle":[],"proceedings-subject":"World Wide Web","short-title":[],"issued":{"date-parts":[[2018]]},"references-count":44,"URL":"https:\/\/doi.org\/10.1145\/3178876.3186015","relation":{},"subject":[],"published":{"date-parts":[[2018]]}}}