{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T11:11:50Z","timestamp":1726053110971},"publisher-location":"Cham","reference-count":37,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030313715"},{"type":"electronic","value":"9783030313722"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-31372-2_24","type":"book-chapter","created":{"date-parts":[[2019,9,27]],"date-time":"2019-09-27T00:02:49Z","timestamp":1569542569000},"page":"286-298","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Prediction Uncertainty Estimation for Hate Speech Classification"],"prefix":"10.1007","author":[{"given":"Kristian","family":"Miok","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong","family":"Nguyen-Doan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bla\u017e","family":"\u0160krlj","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniela","family":"Zaharie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marko","family":"Robnik-\u0160ikonja","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,9,27]]},"reference":[{"key":"24_CR1","unstructured":"Baldi, P., Sadowski, P.J.: Understanding dropout. In: Advances in Neural Information Processing Systems, pp. 2814\u20132822 (2013)"},{"issue":"3","key":"24_CR2","doi-asserted-by":"publisher","first-page":"911","DOI":"10.1111\/j.1467-8659.2011.01940.x","volume":"30","author":"W. Berger","year":"2011","unstructured":"Berger, W., Piringer, H., Filzmoser, P., Gr\u00f6ller, E.: Uncertainty-aware exploration of continuous parameter spaces using multivariate prediction. In: Computer Graphics Forum, pp. 911\u2013920 (2011)","journal-title":"Computer Graphics Forum"},{"key":"24_CR3","first-page":"281","volume":"13","author":"J Bergstra","year":"2012","unstructured":"Bergstra, J., Bengio, Y.: Random search for hyper-parameter optimization. J. Mach. Learn. Res. 13, 281\u2013305 (2012)","journal-title":"J. Mach. Learn. Res."},{"issue":"6","key":"24_CR4","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1080\/1369183X.2011.576195","volume":"37","author":"E Bleich","year":"2011","unstructured":"Bleich, E.: The rise of hate speech and hate crime laws in liberal democracies. J. Ethnic Migr. Stud. 37(6), 917\u2013934 (2011)","journal-title":"J. Ethnic Migr. Stud."},{"key":"24_CR5","unstructured":"Buitinck, L., et al.: API design for machine learning software: experiences from the scikit-learn project. In: ECML PKDD Workshop: Languages for Data Mining and Machine Learning, pp. 108\u2013122 (2013)"},{"key":"24_CR6","unstructured":"Cer, D., et al.: Universal sentence encoder. arXiv preprint arXiv:1803.11175 (2018)"},{"key":"24_CR7","doi-asserted-by":"crossref","unstructured":"Chinchor, N.: Muc-4 evaluation metrics. In: Proceedings of the Fourth Message Understanding Conference, p. 22\u201329 (1992)","DOI":"10.3115\/1072064.1072067"},{"key":"24_CR8","unstructured":"Chollet, F., et al.: Keras (2015). https:\/\/keras.io"},{"key":"24_CR9","doi-asserted-by":"publisher","first-page":"230","DOI":"10.4000\/books.aaccademia.4772","volume-title":"EVALITA Evaluation of NLP and Speech Tools for Italian","author":"Michele Corazza","year":"2018","unstructured":"Corazza, M., et al.: Comparing different supervised approaches to hate speech detection. In: EVALITA 2018 (2018)"},{"issue":"2","key":"24_CR10","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1615\/Int.J.UncertaintyQuantification.2012003966","volume":"3","author":"J Cox","year":"2013","unstructured":"Cox, J., Lindell, M.: Visualizing uncertainty in predicted hurricane tracks. Int. J. Uncertain. Quantif. 3(2), 143\u2013156 (2013)","journal-title":"Int. J. Uncertain. Quantif."},{"key":"24_CR11","doi-asserted-by":"crossref","unstructured":"Davidson, T., Warmsley, D., Macy, M., Weber, I.: Automated hate speech detection and the problem of offensive language. In: Eleventh International AAAI Conference on Web and Social Media (2017)","DOI":"10.1609\/icwsm.v11i1.14955"},{"key":"24_CR12","unstructured":"Del Vigna12, F., Cimino23, A., Dell\u2019Orletta, F., Petrocchi, M., Tesconi, M.: Hate me, hate me not: Hate speech detection on facebook (2017)"},{"key":"24_CR13","unstructured":"Fortunato, M., Blundell, C., Vinyals, O.: Bayesian recurrent neural networks. arXiv preprint arXiv:1704.02798 (2017)"},{"key":"24_CR14","unstructured":"Gal, Y., Ghahramani, Z.: Dropout as a Bayesian approximation: representing model uncertainty in deep learning. In: International Conference on Machine Learning, pp. 1050\u20131059 (2016)"},{"key":"24_CR15","unstructured":"Gal, Y., Ghahramani, Z.: A theoretically grounded application of dropout in recurrent neural networks. In: Advances in Neural Information Processing Systems, pp. 1019\u20131027 (2016)"},{"issue":"1","key":"24_CR16","first-page":"430","volume":"18","author":"A Kucukelbir","year":"2017","unstructured":"Kucukelbir, A., Tran, D., Ranganath, R., Gelman, A., Blei, D.M.: Automatic differentiation variational inference. J. Mach. Learn.Res. 18(1), 430\u2013474 (2017)","journal-title":"J. Mach. Learn. .Res."},{"issue":"9","key":"24_CR17","doi-asserted-by":"publisher","first-page":"2165","DOI":"10.1109\/TVCG.2016.2607204","volume":"23","author":"L Liu","year":"2016","unstructured":"Liu, L., et al.: Uncertainty visualization by representative sampling from prediction ensembles. IEEE Trans. Vis. Comput. Graph. 23(9), 2165\u20132178 (2016)","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"issue":"1","key":"24_CR18","doi-asserted-by":"publisher","first-page":"882","DOI":"10.1109\/TVCG.2018.2865193","volume":"25","author":"L Liu","year":"2019","unstructured":"Liu, L., Padilla, L., Creem-Regehr, S.H., House, D.H.: Visualizing uncertain tropical cyclone predictions using representative samples from ensembles of forecast tracks. IEEE Trans. Vis. Comput. Graph. 25(1), 882\u2013891 (2019)","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"issue":"29","key":"24_CR19","doi-asserted-by":"publisher","first-page":"861","DOI":"10.21105\/joss.00861","volume":"3","author":"L McInnes","year":"2018","unstructured":"McInnes, L., Healy, J., Saul, N., Grossberger, L.: UMAP: Uniform manifold approximation and projection. J. Open Source Softw. 3(29), 861 (2018)","journal-title":"J. Open Source Softw."},{"key":"24_CR20","doi-asserted-by":"crossref","unstructured":"Mehdad, Y., Tetreault, J.: Do characters abuse more than words? In: Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp. 299\u2013303 (2016)","DOI":"10.18653\/v1\/W16-3638"},{"key":"24_CR21","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013)"},{"key":"24_CR22","doi-asserted-by":"crossref","unstructured":"Miok, K.: Estimation of prediction intervals in neural network-based regression models. In: 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), pp. 463\u2013468, September 2018","DOI":"10.1109\/SYNASC.2018.00078"},{"key":"24_CR23","unstructured":"Myshkov, P., Julier, S.: Posterior distribution analysis for Bayesian inference in neural networks. In: Workshop on Bayesian Deep Learning, NIPS (2016)"},{"key":"24_CR24","unstructured":"Peters, M.E., et al.: Deep contextualized word representations. arXiv preprint arXiv:1802.05365 (2018)"},{"key":"24_CR25","doi-asserted-by":"crossref","unstructured":"Pham, V., Bluche, T., Kermorvant, C., Louradour, J.: Dropout improves recurrent neural networks for handwriting recognition. In: 2014 14th International Conference on Frontiers in Handwriting Recognition, pp. 285\u2013290. IEEE (2014)","DOI":"10.1109\/ICFHR.2014.55"},{"key":"24_CR26","doi-asserted-by":"crossref","unstructured":"Platt, J.C.: Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. In: Advances in large margin classifiers, pp. 61\u201374. MIT Press (1999)","DOI":"10.7551\/mitpress\/1113.003.0008"},{"key":"24_CR27","unstructured":"Rehurek, R., Sojka, P.: Software framework for topic modelling with large corpora. In: Proceedings of the LREC 2010 Workshop on New Challenges for NLP Frameworks, pp. 45\u201350. ELRA, Valletta, Malta, May 2010"},{"key":"24_CR28","unstructured":"Rother, K., Allee, M., Rettberg, A.: Ulmfit at germeval-2018: a deep neural language model for the classification of hate speech in German tweets. In: 14th Conference on Natural Language Processing KONVENS 2018, p. 113 (2018)"},{"issue":"2","key":"24_CR29","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1080\/13875868.2015.1137577","volume":"16","author":"IT Ruginski","year":"2016","unstructured":"Ruginski, I.T., et al.: Non-expert interpretations of hurricane forecast uncertainty visualizations. Spat. Cogn. Comput. 16(2), 154\u2013172 (2016)","journal-title":"Spat. Cogn. Comput."},{"key":"24_CR30","doi-asserted-by":"crossref","unstructured":"Schmidt, A., Wiegand, M.: A survey on hate speech detection using natural language processing. In: Proceedings of the Fifth International Workshop on Natural Language Processing for Social Media, pp. 1\u201310 (2017)","DOI":"10.18653\/v1\/W17-1101"},{"issue":"1","key":"24_CR31","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1108\/eb026526","volume":"28","author":"K Sparck Jones","year":"1972","unstructured":"Sparck Jones, K.: A statistical interpretation of term specificity and its application in retrieval. J. Doc. 28(1), 11\u201321 (1972)","journal-title":"J. Doc."},{"issue":"1","key":"24_CR32","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929\u20131958 (2014)","journal-title":"J. Mach. Learn. Res."},{"key":"24_CR33","doi-asserted-by":"publisher","DOI":"10.4159\/harvard.9780674065086","volume-title":"The Harm in Hate Speech","author":"J Waldron","year":"2012","unstructured":"Waldron, J.: The Harm in Hate Speech. Harvard University Press, Cambridge (2012)"},{"key":"24_CR34","unstructured":"Wang, S., Manning, C.: Fast dropout training. In: International Conference on Machine Learning, pp. 118\u2013126 (2013)"},{"key":"24_CR35","unstructured":"Warner, W., Hirschberg, J.: Detecting hate speech on the world wide web. In: Proceedings of the Second Workshop on Language in Social Media, pp. 19\u201326. Association for Computational Linguistics (2012)"},{"key":"24_CR36","unstructured":"Zaremba, W., Sutskever, I., Vinyals, O.: Recurrent neural network regularization. arXiv preprint arXiv:1409.2329 (2014)"},{"key":"24_CR37","doi-asserted-by":"crossref","unstructured":"Zhu, L., Laptev, N.: Deep and confident prediction for time series at uber. In: 2017 IEEE International Conference on Data Mining Workshops (ICDMW), pp. 103\u2013110. IEEE (2017)","DOI":"10.1109\/ICDMW.2017.19"}],"container-title":["Lecture Notes in Computer Science","Statistical Language and Speech Processing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-31372-2_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T03:39:52Z","timestamp":1721792392000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-31372-2_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030313715","9783030313722"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-31372-2_24","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"27 September 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SLSP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Statistical Language and Speech Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ljubljana","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Slovenia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"slsp2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/slsp2019.irdta.eu\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"48","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":"25","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":"1","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":"52% - 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":"4","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}