{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:57:25Z","timestamp":1743105445696,"version":"3.40.3"},"publisher-location":"Cham","reference-count":42,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031353192"},{"type":"electronic","value":"9783031353208"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-35320-8_31","type":"book-chapter","created":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T05:01:53Z","timestamp":1686632513000},"page":"428-442","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Adversarial Capsule Networks for\u00a0Romanian Satire Detection and Sentiment Analysis"],"prefix":"10.1007","author":[{"given":"Sebastian-Vasile","family":"Echim","sequence":"first","affiliation":[]},{"given":"R\u0103zvan-Alexandru","family":"Sm\u0103du","sequence":"additional","affiliation":[]},{"given":"Andrei-Marius","family":"Avram","sequence":"additional","affiliation":[]},{"given":"Dumitru-Clementin","family":"Cercel","sequence":"additional","affiliation":[]},{"given":"Florin","family":"Pop","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,14]]},"reference":[{"key":"31_CR1","unstructured":"Avram, A.M., et al.: Distilling the knowledge of Romanian BERTs using multiple teachers. In: Proceedings of the Thirteenth Language Resources and Evaluation Conference, pp. 374\u2013384 (2022)"},{"key":"31_CR2","doi-asserted-by":"crossref","unstructured":"Butnaru, A., Ionescu, R.T.: MOROCO: the Moldavian and Romanian dialectal corpus. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 688\u2013698 (2019)","DOI":"10.18653\/v1\/P19-1068"},{"key":"31_CR3","doi-asserted-by":"publisher","unstructured":"Cho, K., van Merrienboer, B., Bahdanau, D., Bengio, Y.: On the properties of neural machine translation: encoder-decoder approaches, pp. 103\u2013111 (2014). https:\/\/doi.org\/10.3115\/v1\/W14-4012","DOI":"10.3115\/v1\/W14-4012"},{"key":"31_CR4","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"31_CR5","doi-asserted-by":"crossref","unstructured":"Dumitrescu, S., Avram, A.M., Pyysalo, S.: The birth of Romanian BERT. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 4324\u20134328 (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.387"},{"key":"31_CR6","unstructured":"Dumitrescu, \u015e.D., Avram, A.M.: Introducing RONEC-the Romanian named entity corpus. In: Proceedings of the 12th Language Resources and Evaluation Conference, pp. 4436\u20134443 (2020)"},{"key":"31_CR7","unstructured":"Dumitrescu, S.D., et al.: LiRo: Benchmark and leaderboard for Romanian language tasks. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 1) (2021)"},{"key":"31_CR8","unstructured":"Goodfellow, I.J., Shlens, J., Szegedy, C.: Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572 (2014)"},{"key":"31_CR9","doi-asserted-by":"publisher","unstructured":"Graves, A., Schmidhuber, J.: Framewise phoneme classification with bidirectional LSTM networks. In: Proceedings. 2005 IEEE International Joint Conference on Neural Networks, vol. 4, pp. 2047\u20132052 (2005). https:\/\/doi.org\/10.1109\/IJCNN.2005.1556215","DOI":"10.1109\/IJCNN.2005.1556215"},{"issue":"8","key":"31_CR10","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"key":"31_CR11","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1016\/j.neucom.2019.10.033","volume":"376","author":"J Kim","year":"2020","unstructured":"Kim, J., Jang, S., Park, E., Choi, S.: Text classification using capsules. Neurocomputing 376, 214\u2013221 (2020)","journal-title":"Neurocomputing"},{"key":"31_CR12","doi-asserted-by":"publisher","unstructured":"Kim, Y.: Convolutional neural networks for sentence classification. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1746\u20131751 (2014). https:\/\/doi.org\/10.3115\/v1\/d14-1181","DOI":"10.3115\/v1\/d14-1181"},{"key":"31_CR13","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"31_CR14","unstructured":"Kutuzov, A., Barnes, J., Velldal, E., \u00d8vrelid, L., Oepen, S.: Large-scale contextualised language modelling for Norwegian. arXiv preprint arXiv:2104.06546 (2021)"},{"issue":"1","key":"31_CR15","first-page":"1295","volume":"34","author":"M Kwabena Patrick","year":"2022","unstructured":"Kwabena Patrick, M., Felix Adekoya, A., Abra Mighty, A., Edward, B.Y.: Capsule networks - a survey. J. King Saud Univ. Comput. Inf. Sci. 34(1), 1295\u20131310 (2022)","journal-title":"J. King Saud Univ. Comput. Inf. Sci."},{"key":"31_CR16","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Goyal, P., Girshick, R., He, K., Doll\u00e1r, P.: Focal loss for dense object detection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2980\u20132988 (2017)","DOI":"10.1109\/ICCV.2017.324"},{"key":"31_CR17","unstructured":"Van der Maaten, L., Hinton, G.: Visualizing data using t-SNE. J. Mach. Learn. Res. 9(11), 1\u201327 (2008)"},{"key":"31_CR18","unstructured":"Madry, A., Makelov, A., Schmidt, L., Tsipras, D., Vladu, A.: Towards deep learning models resistant to adversarial attacks. In: 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, 30 April \u2013 3 May 2018, Conference Track Proceedings. OpenReview.net (2018). https:\/\/openreview.net\/forum?id=rJzIBfZAb"},{"key":"31_CR19","doi-asserted-by":"crossref","unstructured":"Masala, M., Ruseti, S., Dascalu, M.: Robert-a Romanian BERT model. In: Proceedings of the 28th International Conference on Computational Linguistics, pp. 6626\u20136637 (2020)","DOI":"10.18653\/v1\/2020.coling-main.581"},{"key":"31_CR20","doi-asserted-by":"publisher","unstructured":"McHardy, R., Adel, H., Klinger, R.: Adversarial training for satire detection: controlling for confounding variables. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 660\u2013665. Association for Computational Linguistics, Minneapolis, Minnesota (2019). https:\/\/doi.org\/10.18653\/v1\/N19-1069","DOI":"10.18653\/v1\/N19-1069"},{"key":"31_CR21","unstructured":"Mititelu, V.B., Tufi\u015f, D., Irimia, E.: The reference corpus of the contemporary Romanian language (CoRoLa). In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) (2018)"},{"key":"31_CR22","unstructured":"Miyato, T., Dai, A.M., Goodfellow, I.J.: Adversarial training methods for semi-supervised text classification. In: 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, 24\u201326 April 2017, Conference Track Proceedings. OpenReview.net (2017)"},{"issue":"4","key":"31_CR23","doi-asserted-by":"publisher","first-page":"57","DOI":"10.3390\/computers11040057","volume":"11","author":"DC Nicolae","year":"2022","unstructured":"Nicolae, D.C., Yadav, R.K., Tufi\u015f, D.: A lite Romanian BERT: ALR-BERT. Computers 11(4), 57 (2022)","journal-title":"Computers"},{"key":"31_CR24","doi-asserted-by":"crossref","unstructured":"Niculescu, M.A., Ruseti, S., Dascalu, M.: Rogpt2: Romanian gpt2 for text generation. In: 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), pp. 1154\u20131161. IEEE (2021)","DOI":"10.1109\/ICTAI52525.2021.00183"},{"key":"31_CR25","doi-asserted-by":"publisher","unstructured":"Onose, C., Cercel, D.C., Trausan-Matu, S.: SC-UPB at the VarDial 2019 evaluation campaign: Moldavian vs. Romanian cross-dialect topic identification. In: Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects, pp. 172\u2013177. Association for Computational Linguistics, Ann Arbor, Michigan (2019). https:\/\/doi.org\/10.18653\/v1\/W19-1418","DOI":"10.18653\/v1\/W19-1418"},{"key":"31_CR26","doi-asserted-by":"crossref","unstructured":"P\u0103i\u015f, V., Mitrofan, M., Gasan, C.L., Coneschi, V., Ianov, A.: Named entity recognition in the Romanian legal domain. In: Proceedings of the Natural Legal Language Processing Workshop 2021, pp. 9\u201318 (2021)","DOI":"10.18653\/v1\/2021.nllp-1.2"},{"key":"31_CR27","doi-asserted-by":"crossref","unstructured":"Rogoz, A.C., Gaman, M., Ionescu, R.T.: SaRoCo: detecting satire in a novel Romanian corpus of news articles. In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. Association for Computational Linguistics, Online (2021). https:\/\/arxiv.org\/pdf\/2105.06456.pdf","DOI":"10.18653\/v1\/2021.acl-short.136"},{"key":"31_CR28","unstructured":"Sabour, S., Frosst, N., Hinton, G.E.: Dynamic routing between capsules. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"issue":"5","key":"31_CR29","doi-asserted-by":"publisher","first-page":"1168","DOI":"10.1109\/TCSS.2020.3014128","volume":"7","author":"T Saha","year":"2020","unstructured":"Saha, T., Ramesh Jayashree, S., Saha, S., Bhattacharyya, P.: Bert-caps: a transformer-based capsule network for tweet act classification. IEEE Trans. Comput. Soc. Syst. 7(5), 1168\u20131179 (2020). https:\/\/doi.org\/10.1109\/TCSS.2020.3014128","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"key":"31_CR30","unstructured":"Srivastava, S., Khurana, P., Tewari, V.: Identifying aggression and toxicity in comments using capsule network. In: Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018), pp. 98\u2013105. Association for Computational Linguistics, Santa Fe, New Mexico, USA (2018). https:\/\/aclanthology.org\/W18-4412"},{"key":"31_CR31","doi-asserted-by":"publisher","first-page":"100551","DOI":"10.1109\/ACCESS.2020.2997675","volume":"8","author":"J Su","year":"2020","unstructured":"Su, J., Yu, S., Luo, D.: Enhancing aspect-based sentiment analysis with capsule network. IEEE Access 8, 100551\u2013100561 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.2997675","journal-title":"IEEE Access"},{"key":"31_CR32","series-title":"Advances in Computer Vision and Pattern Recognition","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1007\/978-3-319-58347-1_8","volume-title":"Domain Adaptation in Computer Vision Applications","author":"B Sun","year":"2017","unstructured":"Sun, B., Feng, J., Saenko, K.: Correlation alignment for unsupervised domain adaptation. In: Csurka, G. (ed.) Domain Adaptation in Computer Vision Applications. ACVPR, pp. 153\u2013171. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-58347-1_8"},{"key":"31_CR33","unstructured":"Szegedy, C., et al.: Intriguing properties of neural networks. In: Bengio, Y., LeCun, Y. (eds.) 2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, 14\u201316 April 2014, Conference Track Proceedings (2014). http:\/\/arxiv.org\/abs\/1312.6199"},{"key":"31_CR34","doi-asserted-by":"crossref","unstructured":"Tache, A., Gaman, M., Ionescu, R.T.: Clustering word embeddings with self-organizing maps. application on LaRoSeDa - a large Romanian sentiment data set. In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pp. 949\u2013956. Association for Computational Linguistics, Online (2021). https:\/\/www.aclweb.org\/anthology\/2021.eacl-main.81","DOI":"10.18653\/v1\/2021.eacl-main.81"},{"key":"31_CR35","doi-asserted-by":"crossref","unstructured":"Wang, A., Singh, A., Michael, J., Hill, F., Levy, O., Bowman, S.: Glue: a multi-task benchmark and analysis platform for natural language understanding. In: Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, pp. 353\u2013355 (2018)","DOI":"10.18653\/v1\/W18-5446"},{"key":"31_CR36","doi-asserted-by":"crossref","unstructured":"Xiao, C., Li, B., Zhu, J.Y., He, W., Liu, M., Song, D.: Generating adversarial examples with adversarial networks. In: 27th International Joint Conference on Artificial Intelligence, IJCAI 2018, pp. 3905\u20133911. International Joint Conferences on Artificial Intelligence (2018)","DOI":"10.24963\/ijcai.2018\/543"},{"key":"31_CR37","doi-asserted-by":"publisher","first-page":"51522","DOI":"10.1109\/ACCESS.2019.2909919","volume":"7","author":"G Xu","year":"2019","unstructured":"Xu, G., Meng, Y., Qiu, X., Yu, Z., Wu, X.: Sentiment analysis of comment texts based on BiLSTM. IEEE Access 7, 51522\u201351532 (2019). https:\/\/doi.org\/10.1109\/ACCESS.2019.2909919","journal-title":"IEEE Access"},{"key":"31_CR38","doi-asserted-by":"publisher","unstructured":"Yang, F., Mukherjee, A., Dragut, E.: Satirical news detection and analysis using attention mechanism and linguistic features. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 1979\u20131989. Association for Computational Linguistics, Copenhagen, Denmark (2017). https:\/\/doi.org\/10.18653\/v1\/D17-1211","DOI":"10.18653\/v1\/D17-1211"},{"key":"31_CR39","unstructured":"Yang, Z., Dai, Z., Yang, Y., Carbonell, J., Salakhutdinov, R.R., Le, Q.V.: XLNET: Generalized autoregressive pretraining for language understanding. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"},{"key":"31_CR40","doi-asserted-by":"publisher","first-page":"58284","DOI":"10.1109\/ACCESS.2018.2874623","volume":"6","author":"B Zhang","year":"2018","unstructured":"Zhang, B., Xu, X., Yang, M., Chen, X., Ye, Y.: Cross-domain sentiment classification by capsule network with semantic rules. IEEE Access 6, 58284\u201358294 (2018). https:\/\/doi.org\/10.1109\/ACCESS.2018.2874623","journal-title":"IEEE Access"},{"key":"31_CR41","doi-asserted-by":"publisher","unstructured":"Zhao, W., Peng, H., Eger, S., Cambria, E., Yang, M.: Towards scalable and reliable capsule networks for challenging NLP applications. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 1549\u20131559. Association for Computational Linguistics, Florence, Italy (2019). https:\/\/doi.org\/10.18653\/v1\/P19-1150","DOI":"10.18653\/v1\/P19-1150"},{"key":"31_CR42","unstructured":"Zhao, W., Ye, J., Yang, M., Lei, Z., Zhang, S., Zhao, Z.: Investigating capsule networks with dynamic routing for text classification. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 3110\u20133119 (2018)"}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-35320-8_31","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T06:08:19Z","timestamp":1686636499000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-35320-8_31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031353192","9783031353208"],"references-count":42,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-35320-8_31","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"14 June 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLDB","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Applications of Natural Language to Information Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Derby","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 June 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 June 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nldb2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.derby.ac.uk\/events\/latest-events\/nldb-2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easy Chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"89","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"31","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"14","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"35% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}