{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T00:57:07Z","timestamp":1743037027421,"version":"3.40.3"},"publisher-location":"Cham","reference-count":39,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030988753"},{"type":"electronic","value":"9783030988760"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-98876-0_13","type":"book-chapter","created":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T09:04:26Z","timestamp":1648717466000},"page":"148-158","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["BERT Model-Based Approach for\u00a0Detecting Racism and\u00a0Xenophobia on\u00a0Twitter Data"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4450-349X","authenticated-orcid":false,"given":"Jos\u00e9 Alberto","family":"Benitez-Andrades","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0955-3432","authenticated-orcid":false,"given":"\u00c1lvaro","family":"Gonz\u00e1lez-Jim\u00e9nez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1488-1120","authenticated-orcid":false,"given":"\u00c1lvaro","family":"L\u00f3pez-Brea","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6514-6858","authenticated-orcid":false,"given":"Carmen","family":"Benavides","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5439-0997","authenticated-orcid":false,"given":"Jose","family":"Aveleira-Mata","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9396-5941","authenticated-orcid":false,"given":"Jos\u00e9-Manuel","family":"Alija-P\u00e9rez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3796-3949","authenticated-orcid":false,"given":"Mar\u00eda Teresa","family":"Garc\u00eda-Ord\u00e1s","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,1]]},"reference":[{"issue":"2","key":"13_CR1","doi-asserted-by":"publisher","first-page":"182","DOI":"10.14569\/IJACSA.2018.090226","volume":"9","author":"M Ahmad","year":"2018","unstructured":"Ahmad, M., Aftab, S., Bashir, M.S., Hameed, N.: Sentiment analysis using SVM: a systematic literature review. Int. J. Adv. Comput. Sci. Appl. 9(2), 182\u2013188 (2018). https:\/\/doi.org\/10.14569\/IJACSA.2018.090226","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"13_CR2","doi-asserted-by":"publisher","unstructured":"Al-Hassan, A., Al-Dossari, H.: Detection of hate speech in social networks: a survey on multilingual corpus. In: Computer Science & Information Technology (CS & IT), pp. 83\u2013100. AIRCC Publishing Corporation, February 2019. https:\/\/doi.org\/10.5121\/csit.2019.90208","DOI":"10.5121\/csit.2019.90208"},{"key":"13_CR3","doi-asserted-by":"publisher","unstructured":"Alotaibi, A., Abul Hasanat, M.H.: Racism detection in Twitter using deep learning and text mining techniques for the Arabic language. In: Proceedings - 2020 1st International Conference of Smart Systems and Emerging Technologies, SMART-TECH 2020, pp. 161\u2013164 (2020). https:\/\/doi.org\/10.1109\/SMART-TECH49988.2020.00047","DOI":"10.1109\/SMART-TECH49988.2020.00047"},{"key":"13_CR4","unstructured":"Anonymous: Finsbury Park attack: son of hire boss held over Facebook post. BBC News (2017). https:\/\/www.bbc.co.uk\/news\/uk-wales-40347813\/"},{"key":"13_CR5","doi-asserted-by":"publisher","unstructured":"del Arco, F.M.P., Molina-Gonz\u00e1lez, M.D., Ure\u00f1a-L\u00f3pez, L.A., Mart\u00edn-Valdivia, M.T.: Comparing pre-trained language models for Spanish hate speech detection. Expert Syst. Appl. 166, 114120 (2021). https:\/\/doi.org\/10.1016\/j.eswa.2020.114120, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S095741742030868X","DOI":"10.1016\/j.eswa.2020.114120"},{"issue":"2","key":"13_CR6","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1037\/a0034335","volume":"4","author":"CP Barlett","year":"2015","unstructured":"Barlett, C.P.: Anonymously hurting others online: the effect of anonymity on cyberbullying frequency. Psychol. Pop. Media Cult. 4(2), 70\u201379 (2015). https:\/\/doi.org\/10.1037\/a0034335","journal-title":"Psychol. Pop. Media Cult."},{"key":"13_CR7","doi-asserted-by":"publisher","unstructured":"Basile, V., et al.: SemEval-2019 task 5: multilingual detection of hate speech against immigrants and women in Twitter. In: Proceedings of the 13th International Workshop on Semantic Evaluation, Minneapolis, Minnesota, USA, pp. 54\u201363. Association for Computational Linguistics, June 2019. https:\/\/doi.org\/10.18653\/v1\/S19-2007","DOI":"10.18653\/v1\/S19-2007"},{"key":"13_CR8","doi-asserted-by":"publisher","unstructured":"Bisht, A., Singh, A., Bhadauria, H.S., Virmani, J., Kriti: Detection of hate speech and offensive language in Twitter data using LSTM model, pp. 243\u2013264. Springer, Singapore (2020). https:\/\/doi.org\/10.1007\/978-981-15-2740-1_17","DOI":"10.1007\/978-981-15-2740-1_17"},{"key":"13_CR9","doi-asserted-by":"publisher","unstructured":"Br Ginting, P.S., Irawan, B., Setianingsih, C.: Hate speech detection on Twitter using multinomial logistic regression classification method. In: 2019 IEEE International Conference on Internet of Things and Intelligence System (IoTaIS), pp. 105\u2013111 (2019). https:\/\/doi.org\/10.1109\/IoTaIS47347.2019.8980379","DOI":"10.1109\/IoTaIS47347.2019.8980379"},{"key":"13_CR10","unstructured":"Ca\u00f1ete, J., Chaperon, G., Fuentes, R., Ho, J.H., Kang, H., P\u00e9rez, J.: Spanish pre-trained BERT model and evaluation data. In: PML4DC at ICLR 2020 (2020)"},{"key":"13_CR11","doi-asserted-by":"publisher","unstructured":"Chaudhry, I.: Hashtagging hate: using Twitter to track racism online. First Monday, vol. 20, no. 2 (2015). https:\/\/doi.org\/10.5210\/fm.v20i2.5450https:\/\/journals.uic.edu\/ojs\/index.php\/fm\/article\/view\/5450","DOI":"10.5210\/fm.v20i2.5450"},{"issue":"3","key":"13_CR12","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1023\/A:1022627411411","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273\u2013297 (1995). https:\/\/doi.org\/10.1023\/A:1022627411411","journal-title":"Mach. Learn."},{"issue":"5","key":"13_CR13","doi-asserted-by":"publisher","first-page":"1322","DOI":"10.1007\/s40615-020-00894-5","volume":"8","author":"S Criss","year":"2020","unstructured":"Criss, S., Michaels, E.K., Solomon, K., Allen, A.M., Nguyen, T.T.: Twitter fingers and echo chambers: exploring expressions and experiences of online racism using Twitter. J. Racial Ethn. Health Disparities 8(5), 1322\u20131331 (2020). https:\/\/doi.org\/10.1007\/s40615-020-00894-5","journal-title":"J. Racial Ethn. Health Disparities"},{"key":"13_CR14","first-page":"86","volume":"1816","author":"F Del Vigna","year":"2017","unstructured":"Del Vigna, F., Cimino, A., Dell\u2019Orletta, F., Petrocchi, M., Tesconi, M.: Hate me, hate me not: hate speech detection on Facebook. CEUR Workshop Proc. 1816, 86\u201395 (2017)","journal-title":"CEUR Workshop Proc."},{"key":"13_CR15","doi-asserted-by":"publisher","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. 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), Minneapolis, Minnesota, pp. 4171\u20134186. Association for Computational Linguistics, June 2019. https:\/\/doi.org\/10.18653\/v1\/N19-1423","DOI":"10.18653\/v1\/N19-1423"},{"key":"13_CR16","unstructured":"de los diputados, C., Government, S., October 2020. https:\/\/www.parlamento2030.es\/initiatives\/3381886de6b06a9ab93ac0bed74cbc61d9259c1c"},{"key":"13_CR17","doi-asserted-by":"publisher","unstructured":"Garcia, K., Berton, L.: Topic detection and sentiment analysis in Twitter content related to COVID-19 from Brazil and the USA. Appl. Soft Comput. 101, 107057 (2021). https:\/\/doi.org\/10.1016\/j.asoc.2020.107057, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1568494620309959","DOI":"10.1016\/j.asoc.2020.107057"},{"issue":"12","key":"13_CR18","doi-asserted-by":"publisher","first-page":"8823","DOI":"10.1007\/s00521-018-3870-x","volume":"31","author":"PJ Garc\u00eda Nieto","year":"2019","unstructured":"Garc\u00eda Nieto, P.J., Garc\u00eda-Gonzalo, E., Paredes-S\u00e1nchez, J.P., Bernardo S\u00e1nchez, A., Men\u00e9ndez Fern\u00e1ndez, M.: Predictive modelling of the higher heating value in biomass torrefaction for the energy treatment process using machine-learning techniques. Neural Comput. Appl. 31(12), 8823\u20138836 (2019). https:\/\/doi.org\/10.1007\/s00521-018-3870-x","journal-title":"Neural Comput. Appl."},{"key":"13_CR19","doi-asserted-by":"publisher","unstructured":"Hasan, M.R., Maliha, M., Arifuzzaman, M.: Sentiment analysis with NLP on Twitter data. In: 2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2), pp. 1\u20134 (2019). https:\/\/doi.org\/10.1109\/IC4ME247184.2019.9036670","DOI":"10.1109\/IC4ME247184.2019.9036670"},{"key":"13_CR20","doi-asserted-by":"crossref","unstructured":"Kalaivani, A., Thenmozhi, D.: SSN_NLP_MLRG at SemEval-2020 task 12: offensive language identification in English, Danish, Greek using BERT and machine learning approach. In: Proceedings of the Fourteenth Workshop on Semantic Evaluation, Barcelona, pp. 2161\u20132170. International Committee for Computational Linguistics (online), December 2020. https:\/\/aclanthology.org\/2020.semeval-1.287","DOI":"10.18653\/v1\/2020.semeval-1.287"},{"key":"13_CR21","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1007\/978-981-15-6318-8_13","volume-title":"Machine Learning, Image Processing, Network Security and Data Sciences","author":"P Kumar","year":"2020","unstructured":"Kumar, P., Singh, A., Kumar, P., Kumar, C.: An explainable machine learning approach for definition extraction. In: Bhattacharjee, A., Borgohain, S.K., Soni, B., Verma, G., Gao, X.-Z. (eds.) MIND 2020. CCIS, vol. 1241, pp. 145\u2013155. Springer, Singapore (2020). https:\/\/doi.org\/10.1007\/978-981-15-6318-8_13"},{"issue":"233","key":"13_CR22","doi-asserted-by":"publisher","first-page":"619","DOI":"10.14419\/ijet.v7i2.33.14849","volume":"7","author":"R Lakshmi","year":"2018","unstructured":"Lakshmi, R., Divya, S.R.B., Valarmathi, R.: Analysis of sentiment in Twitter using logistic regression. Int. J. Eng. Technol. 7(233), 619\u2013621 (2018). https:\/\/doi.org\/10.14419\/ijet.v7i2.33.14849","journal-title":"Int. J. Eng. Technol."},{"key":"13_CR23","doi-asserted-by":"publisher","unstructured":"Men\u00e9ndez Garc\u00eda, L.A., S\u00e1nchez Lasheras, F., Garc\u00eda Nieto, P.J., \u00c1lvarez de Prado, L., Bernardo S\u00e1nchez, A.: Predicting benzene concentration using machine learning and time series algorithms. Mathematics 8(12), 2205 (2020). https:\/\/doi.org\/10.3390\/math8122205","DOI":"10.3390\/math8122205"},{"key":"13_CR24","doi-asserted-by":"publisher","unstructured":"Nedjah, N., Santos, I., de Macedo Mourelle, L.: Sentiment analysis using convolutional neural network via word embeddings. Evol. Intell. (2019). https:\/\/doi.org\/10.1007\/s12065-019-00227-4","DOI":"10.1007\/s12065-019-00227-4"},{"key":"13_CR25","doi-asserted-by":"publisher","unstructured":"Paetzold, G.H., Zampieri, M., Malmasi, S.: UTFPR at SemEval-2019 task 5: hate speech identification with recurrent neural networks. In: Proceedings of the 13th International Workshop on Semantic Evaluation, Minneapolis, Minnesota, USA, pp. 519\u2013523. Association for Computational Linguistics, June 2019. https:\/\/doi.org\/10.18653\/v1\/S19-2093","DOI":"10.18653\/v1\/S19-2093"},{"key":"13_CR26","doi-asserted-by":"publisher","unstructured":"Pereira-Kohatsu, J.C., Quijano-S\u00e1nchez, L., Liberatore, F., Camacho-Collados, M.: Detecting and monitoring hate speech in Twitter. Sensors 19(21) (2019). https:\/\/doi.org\/10.3390\/s19214654","DOI":"10.3390\/s19214654"},{"key":"13_CR27","doi-asserted-by":"publisher","unstructured":"Plaza-Del-Arco, F.M., Molina-Gonz\u00e1lez, M.D., Ure\u00f1a L\u00f3pez, L.A., Mart\u00edn-Valdivia, M.T.: Detecting misogyny and xenophobia in Spanish tweets using language technologies. ACM Trans. Internet Technol. 20(2) (2020). https:\/\/doi.org\/10.1145\/3369869","DOI":"10.1145\/3369869"},{"key":"13_CR28","doi-asserted-by":"publisher","first-page":"642","DOI":"10.1080\/01969722.2021.1949520","volume":"52","author":"S Rastogi","year":"2021","unstructured":"Rastogi, S., Bansal, D.: Visualization of Twitter sentiments on Kashmir territorial conflict. Cybern. Syst. 52, 642\u2013669 (2021). https:\/\/doi.org\/10.1080\/01969722.2021.1949520","journal-title":"Cybern. Syst."},{"issue":"6","key":"13_CR29","doi-asserted-by":"publisher","first-page":"845","DOI":"10.35295\/osls.iisl\/0000-0000-0000-0974","volume":"8","author":"S Rodr\u00edguez Maeso","year":"2018","unstructured":"Rodr\u00edguez Maeso, S.: \u201cEurope\u2019\u2019 and the narrative of the \u201ctrue racist\u2019\u2019: (un-)thinking anti-discrimination law through race. O\u00f1ati Socio-Legal Ser. 8(6), 845\u2013873 (2018). https:\/\/doi.org\/10.35295\/osls.iisl\/0000-0000-0000-0974","journal-title":"O\u00f1ati Socio-Legal Ser."},{"key":"13_CR30","doi-asserted-by":"publisher","first-page":"204951","DOI":"10.1109\/ACCESS.2020.3037073","volume":"8","author":"PK Roy","year":"2020","unstructured":"Roy, P.K., Tripathy, A.K., Das, T.K., Gao, X.: A framework for hate speech detection using deep convolutional neural network. IEEE Access 8, 204951\u2013204962 (2020)","journal-title":"IEEE Access"},{"key":"13_CR31","doi-asserted-by":"publisher","unstructured":"Saha, B.N., Senapati, A., Mahajan, A.: LSTM based deep RNN architecture for election sentiment analysis from Bengali newspaper. In: 2020 International Conference on Computational Performance Evaluation (ComPE), pp. 564\u2013569 (2020). https:\/\/doi.org\/10.1109\/ComPE49325.2020.9200062","DOI":"10.1109\/ComPE49325.2020.9200062"},{"issue":"5","key":"13_CR32","doi-asserted-by":"publisher","first-page":"763","DOI":"10.1080\/01419870.2018.1468568","volume":"42","author":"P Sayan","year":"2019","unstructured":"Sayan, P.: Enforcement of the anti-racism legislation of the European Union against antigypsyism. Ethnic Racial Stud. 42(5), 763\u2013781 (2019). https:\/\/doi.org\/10.1080\/01419870.2018.1468568","journal-title":"Ethnic Racial Stud."},{"issue":"1","key":"13_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/01969722.2017.1412866","volume":"49","author":"M Singh","year":"2018","unstructured":"Singh, M., Bansal, D., Sofat, S.: Who is who on Twitter-spammer, fake or compromised account? A tool to reveal true identity in real-time. Cybern. Syst. 49(1), 1\u201325 (2018). https:\/\/doi.org\/10.1080\/01969722.2017.1412866","journal-title":"Cybern. Syst."},{"key":"13_CR34","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1007\/978-3-030-32381-3_16","volume-title":"Chinese Computational Linguistics","author":"C Sun","year":"2019","unstructured":"Sun, C., Qiu, X., Xu, Y., Huang, X.: How to fine-tune BERT for text classification? In: Sun, M., Huang, X., Ji, H., Liu, Z., Liu, Y. (eds.) CCL 2019. LNCS (LNAI), vol. 11856, pp. 194\u2013206. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-32381-3_16"},{"key":"13_CR35","doi-asserted-by":"crossref","unstructured":"Talita, A., Wiguna, A.: Implementasi algoritma long short-term memory (LSTM) untuk mendeteksi ujaran kebencian (hate speech) pada kasus pilpres 2019. MATRIK: Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer 19(1), 37\u201344 (2019). https:\/\/doi.org\/10.30812\/matrik.v19i1.495","DOI":"10.30812\/matrik.v19i1.495"},{"key":"13_CR36","unstructured":"Travis, A.: Anti-Muslim hate crime surges after Manchester and London bridge. The Guardian (2017). https:\/\/www.theguardian.com\/society\/2017\/jun\/20\/anti-muslim-hate-surges-after-manchester-and-london-bridge-attacks"},{"key":"13_CR37","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Guyon, I., et al (eds.) Advances in Neural Information Processing Systems, vol. 30. Curran Associates, Inc. (2017). https:\/\/proceedings.neurips.cc\/paper\/2017\/file\/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf"},{"key":"13_CR38","doi-asserted-by":"publisher","first-page":"13825","DOI":"10.1109\/ACCESS.2018.2806394","volume":"6","author":"H Watanabe","year":"2018","unstructured":"Watanabe, H., Bouazizi, M., Ohtsuki, T.: Hate speech on Twitter: a pragmatic approach to collect hateful and offensive expressions and perform hate speech detection. IEEE Access 6, 13825\u201313835 (2018). https:\/\/doi.org\/10.1109\/ACCESS.2018.2806394","journal-title":"IEEE Access"},{"issue":"5","key":"13_CR39","doi-asserted-by":"publisher","first-page":"925","DOI":"10.3233\/SW-180338","volume":"10","author":"Z Zhang","year":"2019","unstructured":"Zhang, Z., Luo, L.: Hate speech detection: a solved problem? The challenging case of long tail on Twitter. Semantic Web 10(5), 925\u2013945 (2019). https:\/\/doi.org\/10.3233\/SW-180338","journal-title":"Semantic Web"}],"container-title":["Communications in Computer and Information Science","Metadata and Semantic Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-98876-0_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T09:10:30Z","timestamp":1648717830000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-98876-0_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030988753","9783030988760"],"references-count":39,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-98876-0_13","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"1 April 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MTSR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Research Conference on Metadata and Semantics Research","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Madrid","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 November 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mtsr2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.mtsr-conf.org\/2021\/home","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-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":"92","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":"27","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":"7","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":"29% - 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":"2.7","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the COVID-19 pandemic the conference was held online.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}