{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T19:38:11Z","timestamp":1769283491102,"version":"3.49.0"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T00:00:00Z","timestamp":1769126400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T00:00:00Z","timestamp":1769126400000},"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":["Knowl Inf Syst"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1007\/s10115-026-02682-9","type":"journal-article","created":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T09:57:10Z","timestamp":1769162230000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep active learning for identifying hate and offensive content in multilingual social media posts"],"prefix":"10.1007","volume":"68","author":[{"given":"Kirti","family":"Kumari","sequence":"first","affiliation":[]},{"given":"Jyoti Prakash","family":"Singh","sequence":"additional","affiliation":[]},{"given":"Abhinav","family":"Kumar","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,23]]},"reference":[{"key":"2682_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2019.05.009","volume":"36","author":"K Sailunaz","year":"2019","unstructured":"Sailunaz K, Alhajj R (2019) Emotion and sentiment analysis from twitter text. Journal of Computational Science 36:101003. https:\/\/doi.org\/10.1016\/j.jocs.2019.05.009 (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1877750318311037)","journal-title":"Journal of Computational Science"},{"key":"2682_CR2","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1016\/j.jocs.2017.01.010","volume":"21","author":"VK Jain","year":"2017","unstructured":"Jain VK, Kumar S, Fernandes SL (2017) Extraction of emotions from multilingual text using intelligent text processing and computational linguistics. Journal of Computational Science 21:316\u2013326. https:\/\/doi.org\/10.1016\/j.jocs.2017.01.010 (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1877750317301035)","journal-title":"Journal of Computational Science"},{"key":"2682_CR3","doi-asserted-by":"crossref","unstructured":"Saumya S, Kumar A, Singh JP (2024) Filtering offensive language from multilingual social media contents: A deep learning approach. Engineering Applications of Artificial Intelligence 133:108159, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0952197624003178","DOI":"10.1016\/j.engappai.2024.108159"},{"key":"2682_CR4","unstructured":"Kumar R, Reganti AN, Bhatia A, Maheshwari T (2018) Aggression-annotated corpus of Hindi-English code-mixed data. In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), European Language Resources Association (ELRA), Miyazaki, Japan, https:\/\/www.aclweb.org\/anthology\/L18-1226"},{"issue":"5","key":"2682_CR5","first-page":"1821","volume":"105","author":"M Huang","year":"2024","unstructured":"Huang M (2024) Motivation and personality: A comparative study of social media use and misinformation in the united states and china. Soc Sci Q 105(5):1821","journal-title":"Soc Sci Q"},{"key":"2682_CR6","doi-asserted-by":"crossref","unstructured":"Roy PK (2024) An advanced learning approach for detecting sarcasm in social media posts: Theory and solutions. Social Science Quarterly","DOI":"10.1111\/ssqu.13442"},{"key":"2682_CR7","doi-asserted-by":"crossref","unstructured":"Kumar A, Sachdeva N (2019) Cyberbullying detection on social multimedia using soft computing techniques: a meta-analysis. Multimedia Tools and Applications pp 1\u201338","DOI":"10.1007\/s11042-019-7234-z"},{"issue":"3","key":"2682_CR8","doi-asserted-by":"publisher","first-page":"724","DOI":"10.1111\/j.1540-6237.2010.00716.x","volume":"91","author":"A Harell","year":"2010","unstructured":"Harell A (2010) Political tolerance, racist speech, and the influence of social networks. Soc Sci Q 91(3):724\u2013740","journal-title":"Soc Sci Q"},{"issue":"12","key":"2682_CR9","doi-asserted-by":"publisher","first-page":"4180","DOI":"10.3390\/app10124180","volume":"10","author":"K Florio","year":"2020","unstructured":"Florio K, Basile V, Polignano M, Basile P, Patti V (2020) Time of your hate: The challenge of time in hate speech detection on social media. Appl Sci 10(12):4180","journal-title":"Appl Sci"},{"key":"2682_CR10","doi-asserted-by":"crossref","unstructured":"Badjatiya P, Gupta S, Gupta M, Varma V (2017) Deep learning for hate speech detection in tweets. In: Proceedings of the 26th International Conference on World Wide Web Companion, International World Wide Web Conferences Steering Committee, pp 759\u2013760","DOI":"10.1145\/3041021.3054223"},{"issue":"2","key":"2682_CR11","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1002\/poi3.85","volume":"7","author":"P Burnap","year":"2015","unstructured":"Burnap P, Williams ML (2015) Cyber hate speech on Twitter: An application of machine classification and statistical modeling for policy and decision making. Policy & Internet 7(2):223\u2013242","journal-title":"Policy & Internet"},{"key":"2682_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/0952813X.2017.1409284","volume":"30","author":"S Malmasi","year":"2018","unstructured":"Malmasi S, Zampieri M (2018) Challenges in Discriminating Profanity from Hate Speech. Journal of Experimental & Theoretical Artificial Intelligence 30:1\u201316","journal-title":"Journal of Experimental & Theoretical Artificial Intelligence"},{"key":"2682_CR13","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1016\/j.chb.2016.05.051","volume":"63","author":"MA Al-garadi","year":"2016","unstructured":"Al-garadi MA, Varathan KD (2016) Ravana SD (2016) Cybercrime detection in online communications: The experimental case of cyberbullying detection in the Twitter network. Comput Hum Behav 63:433\u2013443","journal-title":"Comput Hum Behav"},{"key":"2682_CR14","doi-asserted-by":"crossref","unstructured":"Davidson T, Warmsley D, Macy M, Weber I (2017) Automated hate speech detection and the problem of offensive language. In: Eleventh International AAAI Conference on Web and Social Media, pp 512\u2013515","DOI":"10.1609\/icwsm.v11i1.14955"},{"key":"2682_CR15","doi-asserted-by":"crossref","unstructured":"Waseem Z, Hovy D (2016) Hateful symbols or hateful people? predictive features for hate speech detection on Twitter. In: Proceedings of the NAACL student research workshop, pp 88\u201393","DOI":"10.18653\/v1\/N16-2013"},{"issue":"3","key":"2682_CR16","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1109\/TAFFC.2016.2531682","volume":"8","author":"R Zhao","year":"2017","unstructured":"Zhao R, Mao K (2017) Cyberbullying detection based on semantic-enhanced marginalized denoising auto-encoder. IEEE Trans Affect Comput 8(3):328\u2013339","journal-title":"IEEE Trans Affect Comput"},{"issue":"1","key":"2682_CR17","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1007\/s13278-024-01264-3","volume":"14","author":"P Kakati","year":"2024","unstructured":"Kakati P, Dandotiya D (2024) Automatic detection of hate speech in code-mixed indian languages in twitter social media interaction using dconvblstm-muril ensemble method. Soc Netw Anal Min 14(1):108","journal-title":"Soc Netw Anal Min"},{"key":"2682_CR18","unstructured":"Chiril P, Benamara F, Moriceau V, Coulomb-Gully M, Kumar A (2019) Multilingual and multitarget hate speech detection in tweets. In: Conf\u00e9rence sur le Traitement Automatique des Langues Naturelles (TALN-PFIA 2019), ATALA, pp 351\u2013360"},{"key":"2682_CR19","doi-asserted-by":"publisher","first-page":"1425","DOI":"10.18653\/v1\/2020.semeval-1.188","volume":"2020","author":"M Zampieri","year":"2020","unstructured":"Zampieri M, Nakov P, Rosenthal S, Atanasova P, Karadzhov G, Mubarak H, Derczynski L, Pitenis Z, \u00c7\u00f6ltekin \u00c7 (2020) Semeval-2020 task 12: Multilingual offensive language identification in social media (offenseval 2020). Proceedings of the Fourteenth Workshop on Semantic Evaluation 2020:1425\u20131447","journal-title":"Proceedings of the Fourteenth Workshop on Semantic Evaluation"},{"key":"2682_CR20","unstructured":"Modha S, Majumder P, Mandl T (2018) Filtering aggression from the multilingual social media feed. In: Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018), pp 199\u2013207"},{"issue":"1","key":"2682_CR21","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1007\/s10844-022-00755-z","volume":"60","author":"R Pandey","year":"2023","unstructured":"Pandey R, Singh JP (2023) Bert-lstm model for sarcasm detection in code-mixed social media post. Journal of Intelligent Information Systems 60(1):235\u2013254","journal-title":"Journal of Intelligent Information Systems"},{"issue":"1","key":"2682_CR22","doi-asserted-by":"publisher","first-page":"26","DOI":"10.29244\/ijsa.v5i1p26-38","volume":"5","author":"MI Abidin","year":"2021","unstructured":"Abidin MI, Notodiputro KA, Sartono B (2021) Improving classification model performances using an active learning method to detect hate speech in twitter: Peningkatan kinerja model klasifikasi dengan pembelajaran aktif dalam mendeteksi ujaran kebencian di twitter. Indonesian Journal of Statistics and Its Applications 5(1):26\u201338","journal-title":"Indonesian Journal of Statistics and Its Applications"},{"key":"2682_CR23","unstructured":"Kirk HR, Vidgen B, Hale SA (2022) Is more data better? re-thinking the importance of efficiency in abusive language detection with transformers-based active learning. arXiv preprint arXiv:2209.10193"},{"key":"2682_CR24","doi-asserted-by":"crossref","unstructured":"ElSherief M, Nilizadeh S, Nguyen D, Vigna G, Belding E (2018) Peer to peer hate: Hate speech instigators and their targets. In: Twelfth International AAAI Conference on Web and Social Media, pp 52\u201361","DOI":"10.1609\/icwsm.v12i1.15038"},{"key":"2682_CR25","unstructured":"Kumari K, Singh JP (2020) AI_ML_NIT_Patna@ HASOC 2020: BERT Models for Hate Speech Identification in Indo-European Languages. In: FIRE (Working Notes), pp 319\u2013324"},{"key":"2682_CR26","doi-asserted-by":"crossref","unstructured":"Bohra A, Vijay D, Singh V, Akhtar SS, Shrivastava M (2018) A Dataset of Hindi-English Code-Mixed Social Media Text for Hate Speech Detection. In: Proceedings of the Second Workshop on Computational Modeling of People\u2019s Opinions, Personality, and Emotions in Social Media, pp 36\u201341","DOI":"10.18653\/v1\/W18-1105"},{"key":"2682_CR27","doi-asserted-by":"crossref","unstructured":"Kwok I, Wang Y (2013) Locate the hate: Detecting tweets against blacks. In: Twenty-seventh AAAI conference on artificial intelligence, pp 1621\u20131622","DOI":"10.1609\/aaai.v27i1.8539"},{"key":"2682_CR28","doi-asserted-by":"crossref","unstructured":"Greevy E, Smeaton AF (2004) Classifying racist texts using a Support Vector Machine. In: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, pp 468\u2013469","DOI":"10.1145\/1008992.1009074"},{"issue":"1","key":"2682_CR29","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1140\/epjds\/s13688-016-0072-6","volume":"5","author":"P Burnap","year":"2016","unstructured":"Burnap P, Williams ML (2016) Us and them: identifying cyber hate on Twitter across multiple protected characteristics. EPJ Data science 5(1):11","journal-title":"EPJ Data science"},{"key":"2682_CR30","doi-asserted-by":"crossref","unstructured":"Founta AM, Djouvas C, Chatzakou D, Leontiadis I, Blackburn J, Stringhini G, Vakali A, Sirivianos M, Kourtellis N (2018) Large scale crowdsourcing and characterization of Twitter abusive behavior. In: Twelfth International AAAI Conference on Web and Social Media, pp 491\u2013500","DOI":"10.1609\/icwsm.v12i1.14991"},{"key":"2682_CR31","doi-asserted-by":"crossref","unstructured":"Chatzakou D, Kourtellis N, Blackburn J, De\u00a0Cristofaro E, Stringhini G, Vakali A (2017) Hate is not binary: Studying abusive behavior of #gamergate on Twitter. In: Proceedings of the 28th ACM conference on hypertext and social media, ACM, pp 65\u201374","DOI":"10.1145\/3078714.3078721"},{"issue":"1","key":"2682_CR32","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1007\/s13278-018-0496-z","volume":"8","author":"YN Silva","year":"2018","unstructured":"Silva YN, Hall DL, Rich C (2018) Bullyblocker: toward an interdisciplinary approach to identify cyberbullying. Soc Netw Anal Min 8(1):18","journal-title":"Soc Netw Anal Min"},{"key":"2682_CR33","unstructured":"Ranasinghe T, Zampieri M, Hettiarachchi H (2019) Brums at hasoc 2019: Deep learning models for multilingual hate speech and offensive language identification. In: FIRE (working notes), pp 199\u2013207"},{"key":"2682_CR34","doi-asserted-by":"crossref","unstructured":"Mehdad Y, Tetreault J (2016) 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","DOI":"10.18653\/v1\/W16-3638"},{"key":"2682_CR35","unstructured":"Yuan S, Wu X, Xiang Y (2016) A Two Phase Deep Learning Model for Identifying Discrimination from Tweets. In: Proceedings of the 19th International Conference on Extending Database Technology (EDBT), pp 696\u2013697"},{"key":"2682_CR36","unstructured":"Del\u00a0Vigna12 F, Cimino23 A, Dell\u2019Orletta F, Petrocchi M, Tesconi M (2017) Hate me, hate me not: Hate speech detection on facebook. In: Proceedings of the first Italian conference on cybersecurity (ITASEC17), pp 86\u201395"},{"key":"2682_CR37","doi-asserted-by":"crossref","unstructured":"Gamb\u00e4ck B, Sikdar UK (2017) Using convolutional neural networks to classify hate-speech. In: Proceedings of the First Workshop on Abusive Language Online, pp 85\u201390","DOI":"10.18653\/v1\/W17-3013"},{"key":"2682_CR38","doi-asserted-by":"crossref","unstructured":"Zhang Z, Robinson D, Tepper J (2018) Detecting hate speech on Twitter using a convolution-gru based deep neural network. In: European semantic web conference, Springer, pp 745\u2013760","DOI":"10.1007\/978-3-319-93417-4_48"},{"key":"2682_CR39","doi-asserted-by":"crossref","unstructured":"Chen H, McKeever S, Delany SJ (2019) The use of deep learning distributed representations in the identification of abusive text. In: Proceedings of the International AAAI Conference on Web and Social Media, vol 13(1), pp 125\u2013133","DOI":"10.1609\/icwsm.v13i01.3215"},{"key":"2682_CR40","unstructured":"Mishra S, Mishra S (2019) 3idiots at hasoc 2019: Fine-tuning transformer neural networks for hate speech identification in indo-european languages. In: Proceedings of the 11th annual meeting of the Forum for Information Retrieval Evaluation (December 2019)"},{"issue":"8","key":"2682_CR41","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0237861","volume":"15","author":"M Mozafari","year":"2020","unstructured":"Mozafari M, Farahbakhsh R, Crespi N (2020) Hate speech detection and racial bias mitigation in social media based on bert model. PLoS ONE 15(8):e0237861","journal-title":"PLoS ONE"},{"key":"2682_CR42","unstructured":"Ezike T, Sivanesan M (2020) Chrestotes@ hasoc 2020: Bert fine-tuning for the identification of hate speech and offensive language in indo-european languages. In: Fire (Working Notes), pp 175\u2013179"},{"key":"2682_CR43","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1109\/MIC.2024.3450090","volume":"28","author":"YM Cetinkaya","year":"2017","unstructured":"Cetinkaya YM, Lee Y, Kulah E, Toroslu IH, Cowan MA, Davulcu H (2017) Toward a Programmable Humanizing Artificial Intelligence Through Scalable Stance-Directed Architecture. IEEE Internet Comput 28:20\u201327","journal-title":"IEEE Internet Comput"},{"key":"2682_CR44","doi-asserted-by":"crossref","unstructured":"Mandl T, Modha S, Patel D, Dave M, Mandlia C, Patel A (2019) Overview of the HASOC track at FIRE 2019: Hate Speech and Offensive Content Identification in Indo-European Languages. In: Proceedings of the 11th annual meeting of the Forum for Information Retrieval Evaluation","DOI":"10.1145\/3368567.3368584"},{"key":"2682_CR45","doi-asserted-by":"crossref","unstructured":"Mandl T, Modha S, Kumar\u00a0M A, Chakravarthi BR (2020a) Overview of the hasoc track at fire 2020: Hate speech and offensive language identification in tamil, malayalam, hindi, english and german. In: Proceedings of the 12th Annual Meeting of the Forum for Information Retrieval Evaluation, pp 29\u201332","DOI":"10.1145\/3441501.3441517"},{"key":"2682_CR46","doi-asserted-by":"crossref","unstructured":"Mandl T, Modha S, Kumar\u00a0M A, Chakravarthi BR (2020b) Overview of the hasoc track at fire 2020: Hate speech and offensive language identification in tamil, malayalam, hindi, english and german. In: Proceedings of the 12th Annual Meeting of the Forum for Information Retrieval Evaluation, pp 29\u201332","DOI":"10.1145\/3441501.3441517"},{"key":"2682_CR47","unstructured":"Devlin J, Chang MW, Lee K, Toutanova K (2018) Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805"},{"key":"2682_CR48","doi-asserted-by":"publisher","unstructured":"Kuruva A, Chiluka CN (2024) Hybrid deep learning approach for sentiment analysis using text and emojis. Network: Computation in Neural Systems 1\u201330. https:\/\/doi.org\/10.1080\/0954898X.2024.2349275","DOI":"10.1080\/0954898X.2024.2349275"},{"key":"2682_CR49","unstructured":"Mishra AK, Saumya S, Kumar A (2020) Iiit_dwd@ hasoc 2020: Identifying offensive content in indo-european languages. In: FIRE (Working Notes), pp 139\u2013144"},{"key":"2682_CR50","unstructured":"Raj R, Srivastava S, Saumya S (2020) Nsit & iiitdwd@ hasoc 2020: Deep learning model for hate-speech identification in indo-european languages. In: FIRE (Working Notes), pp 161\u2013167"},{"key":"2682_CR51","unstructured":"Kumar R, Lahiri B, Ojha AK, Bansal A (2020) Comma@ fire 2020: Exploring multilingual joint training across different classification tasks. In: FIRE (Working Notes), pp 823\u2013828"},{"key":"2682_CR52","unstructured":"Sai S, Sharma Y (2020) Siva@ hasoc-dravidian-codemix-fire-2020: Multilingual offensive speech detection in code-mixed and romanized text. In: FIRE (Working Notes), pp 336\u2013343"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-026-02682-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10115-026-02682-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-026-02682-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T09:57:16Z","timestamp":1769162236000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10115-026-02682-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,23]]},"references-count":52,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,12]]}},"alternative-id":["2682"],"URL":"https:\/\/doi.org\/10.1007\/s10115-026-02682-9","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,23]]},"assertion":[{"value":"7 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 December 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 January 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 January 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors of this manuscript declare that there is no Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interests"}},{"value":"The current research does not require ethical approval as it does not involve any human or animal subjects.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}}],"article-number":"67"}}