{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T10:04:46Z","timestamp":1783159486505,"version":"3.54.6"},"reference-count":58,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T00:00:00Z","timestamp":1679616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Big Data"],"abstract":"<jats:p>Natural language processing (NLP) is a rapidly evolving field at the intersection of linguistics, computer science, and artificial intelligence, which is concerned with developing methods to process and generate language at scale. Modern NLP tools have the potential to support humanitarian action at multiple stages of the humanitarian response cycle. Both internal reports, secondary text data (e.g., social media data, news media articles, or interviews with affected individuals), and external-facing documents like Humanitarian Needs Overviews (HNOs) encode information relevant to monitoring, anticipating, or responding to humanitarian crises. Yet, lack of awareness of the concrete opportunities offered by state-of-the-art techniques, as well as constraints posed by resource scarcity, limit adoption of NLP tools in the humanitarian sector. This paper provides a pragmatically-minded primer to the emerging field of humanitarian NLP, reviewing existing initiatives in the space of humanitarian NLP, highlighting potentially impactful applications of NLP in the humanitarian sector, and describing criteria, challenges, and potential solutions for large-scale adoption. In addition, as one of the main bottlenecks is the lack of data and standards for this domain, we present recent initiatives (the <jats:sc>DEEP<\/jats:sc> and <jats:sc>HumSet<\/jats:sc>) which are directly aimed at addressing these gaps. With this work, we hope to motivate humanitarians and NLP experts to create long-term impact-driven synergies and to co-develop an ambitious roadmap for the field.<\/jats:p>","DOI":"10.3389\/fdata.2023.1082787","type":"journal-article","created":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T05:51:10Z","timestamp":1679637070000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":19,"title":["Natural language processing for humanitarian action: Opportunities, challenges, and the path toward humanitarian NLP"],"prefix":"10.3389","volume":"6","author":[{"given":"Roberta","family":"Rocca","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicol\u00f2","family":"Tamagnone","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Selim","family":"Fekih","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ximena","family":"Contla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Navid","family":"Rekabsaz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,3,24]]},"reference":[{"key":"B1","first-page":"923","article-title":"\u201cCrisisbench: Benchmarking crisis-related social media datasets for humanitarian information processing,\u201d","volume-title":"ICWSM","author":"Alam","year":"2021"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1903.10676","article-title":"Scibert: a pretrained language model for scientific text","author":"Beltagy","year":"2019","journal-title":"arXiv preprint"},{"key":"B3","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1145\/3442188.3445922","article-title":"\u201cOn the dangers of stochastic parrots: can language models be too big?,\u201d","volume-title":"Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency","author":"Bender","year":"2021"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2005.14050","article-title":"Language (technology) is power: a critical survey of \u201cbias\u201d in NLP","author":"Blodgett","year":"2020","journal-title":"arXiv Preprint"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1607.04606","article-title":"Enriching word vectors with subword information","author":"Bojanowski","year":"2016","journal-title":"arXiv Preprint"},{"key":"B6","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1146\/annurev-linguistics-011619-030303","article-title":"Distributional semantics and linguistic theory","volume":"6","author":"Boleda","year":"2020","journal-title":"Annu. Rev. Linguist."},{"key":"B7","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1162\/COLI_a_00261","article-title":"Formal distributional semantics: introduction to the special issue","volume":"42","author":"Boleda","year":"2016","journal-title":"Comput. Linguist."},{"key":"B8","volume-title":"Interactive Voice Response in Humanitarian Contexts.","author":"Bolton","year":"2018"},{"key":"B9","article-title":"\u201cMan is to computer programmer as woman is to homemaker? Debiasing word embeddings,\u201d","volume-title":"30th Conference on Neural Information Processing Systems (NIPS 2016)","author":"Bolukbasi","year":"2016"},{"key":"B10","article-title":"\u201cLanguage models are few-shot learners,\u201d","volume-title":"Advances in Neural Information Processing Systems 33 (NeurIPS 2020)","author":"Brown","year":"2020"},{"key":"B11","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9781316476840","volume-title":"Big Crisis Data: Social Media in Disasters and Time-Critical Situations","author":"Castillo","year":"2016"},{"key":"B12","doi-asserted-by":"crossref","first-page":"8440","DOI":"10.18653\/v1\/2020.acl-main.747","article-title":"\u201cUnsupervised cross-lingual representation learning at scale,\u201d","volume-title":"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics","author":"Conneau","year":"2020"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2207.04672","article-title":"No language left behind: scaling human-centered machine translation","author":"Costa-juss\u00e0","year":"2022","journal-title":"arXiv Preprint"},{"key":"B14","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1186\/s13742-016-0121-x","article-title":"Brainhack: a collaborative workshop for the open neuroscience community","volume":"5","author":"Craddock","year":"2016","journal-title":"GigaSci."},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1905.12516","article-title":"Racial bias in hate speech and abusive language detection datasets","author":"Davidson","year":"2019","journal-title":"arXiv Preprint"},{"key":"B16","article-title":"\u201cBERT: Pre-training of deep bidirectional transformers for language understanding,\u201d","volume-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics","author":"Devlin","year":"2019"},{"key":"B17","doi-asserted-by":"publisher","first-page":"11203","DOI":"10.1073\/pnas.1802331115","article-title":"Facebook language predicts depression in medical records","volume":"115","author":"Eichstaedt","year":"2018","journal-title":"Proc. Natl. Acad. Sci. U.S.A."},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2210.04573","article-title":"Humset: Dataset of multilingual information extraction and classification for humanitarian crisis response","author":"Fekih","year":"2022","journal-title":"arXiv Preprint"},{"key":"B19","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1080\/00437956.1954.11659520","article-title":"Distributional structure","volume":"10","author":"Harris","year":"1954","journal-title":"Word"},{"key":"B20","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1145\/2567948.2577034","article-title":"\u201cAIDR: Artificial intelligence for disaster response,\u201d","volume-title":"Proceedings of the 23rd International Conference on World Wide Web","author":"Imran","year":"2014"},{"key":"B21","doi-asserted-by":"crossref","DOI":"10.4324\/9781315638423-2","article-title":"\u201cThe use of social media for crisis management,\u201d","volume-title":"Big Data, Surveillance and Crisis Management","author":"Imran","year":"2017"},{"key":"B22","article-title":"Twitter as a lifeline: human-annotated twitter corpora for NLP of crisis-related messages","volume-title":"arXiv Preprint","author":"Imran","year":"2016"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2004.09095","article-title":"The state and fate of linguistic diversity and inclusion in the NLP world","author":"Joshi","year":"2020","journal-title":"arXiv Preprint"},{"key":"B24","volume-title":"Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition","author":"Jurafsky","year":"2000"},{"key":"B25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3430263.3452414","article-title":"\u201cLoud and clear: the missing links of language and language technology for humanitarian access, impact, and accountability,\u201d","volume-title":"Proceedings of the 18th International Web for All Conference","author":"Kemp","year":"2021"},{"key":"B26","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1147\/JRD.2019.2947014","article-title":"Improving humanitarian needs assessments through natural language processing","volume":"64","author":"Kreutzer","year":"2019","journal-title":"IBM J. Res. Dev."},{"key":"B27","doi-asserted-by":"publisher","first-page":"102735","DOI":"10.1016\/j.ipm.2021.102735","article-title":"A natural language processing approach to understanding context in the extraction and geocoding of historical floods, storms, and adaptation measures","volume":"59","author":"Lai","year":"2022","journal-title":"Inform. Process. Manage."},{"key":"B28","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2003.14402","article-title":"Low resource neural machine translation: a benchmark for five african languages","author":"Lakew","year":"2020","journal-title":"arXiv Preprint"},{"key":"B29","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1037\/0033-295X.104.2.211","article-title":"A solution to Plato's problem: the latent semantic analysis theory of acquisition, induction, and representation of knowledge","volume":"104","author":"Landauer","year":"1997","journal-title":"Psychol. Rev."},{"key":"B30","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1907.11692","article-title":"RoBERTa: a robustly optimized bert pretraining approach","author":"Liu","year":"2019","journal-title":"arXiv Preprint"},{"key":"B32","doi-asserted-by":"crossref","DOI":"10.4324\/9780429279188","volume-title":"Understanding the Humanitarian World","author":"Maxwell","year":"2019"},{"key":"B33","doi-asserted-by":"crossref","DOI":"10.1201\/b18023","volume-title":"Digital Humanitarians: How Big Data is Changing the Face of Humanitarian Response","author":"Meier","year":"2015"},{"key":"B34","article-title":"\u201cDistributed representations of words and phrases and their compositionality,\u201d","volume-title":"NIPS'13: Proceedings of the 26th International Conference on Neural Information Processing Systems","author":"Mikolov","year":"2013"},{"key":"B35","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2111.01243","article-title":"Recent advances in natural language processing via large pre-trained language models: a survey","author":"Min","year":"2021","journal-title":"arXiv."},{"key":"B36","doi-asserted-by":"crossref","DOI":"10.18653\/v1\/2022.naacl-main.293","article-title":"\u201cWECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models,\u201d","volume-title":"Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics","author":"Minixhofer","year":"2022"},{"key":"B37","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2010.02353","article-title":"Participatory research for low-resourced machine translation: a case study in african languages","author":"Nekoto","year":"2020","journal-title":"arXiv Preprint"},{"key":"B38","doi-asserted-by":"crossref","DOI":"10.1109\/GHTC46280.2020.9342939","article-title":"\u201cGamayun-language technology for humanitarian response,\u201d","volume-title":"2020 IEEE Global Humanitarian Technology Conference (GHTC)","author":"\u00d6ktem","year":"2020"},{"key":"B39","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2007.11756","article-title":"Clustering of social media messages for humanitarian aid response during crisis","author":"Padhee","year":"2020","journal-title":"arXiv Preprint"},{"key":"B40","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2022.07.002","article-title":"Speech disturbances in schizophrenia: assessing cross-linguistic generalizability of NLP automated measures of coherence","author":"Parola","year":"2022","journal-title":"Schizophr. Res."},{"key":"B41","doi-asserted-by":"crossref","DOI":"10.3115\/v1\/D14-1162","article-title":"\u201cGloVe: Global vectors for word representation,\u201d","volume-title":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","author":"Pennington","year":"2014"},{"key":"B42","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1186\/s41018-016-0013-9","article-title":"Crisis analytics: big data-driven crisis response","volume":"1","author":"Qadir","year":"2016","journal-title":"J. Int. Hum. Act."},{"key":"B43","unstructured":"RadfordA.\n            WuJ.\n            ChildR.\n            LuanD.\n            AmodeiD.\n            SutskeverI.\n          35637722Language Models are Unsupervised Multitask Learners2019"},{"key":"B44","unstructured":"RoccaR.\n          Complex Systems Modeling for Humanitarian Action: Methods and Opportunities. Technical Report, Centre for Humanitarian Data2022"},{"key":"B45","doi-asserted-by":"publisher","first-page":"1121","DOI":"10.1080\/02699930441000030","article-title":"Language use of depressed and depression-vulnerable college students","volume":"18","author":"Rude","year":"2004","journal-title":"Cognit. Emot."},{"key":"B46","unstructured":"RuderS.\n          31537505A Review of the Neural History of Natural Language Processing"},{"key":"B47","unstructured":"RuderS.\n          NLP's ImageNet Moment has Arrived"},{"key":"B48","first-page":"15","article-title":"\u201cTransfer learning in natural language processing,\u201d","author":"Ruder","year":"2019","journal-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorials"},{"key":"B49","first-page":"787","article-title":"\u201cDimensions of meaning,\u201d","volume-title":"Proceedings of the 1992 ACM\/IEEE Conference on Supercomputing","author":"Sch\u00fctze","year":"1992"},{"key":"B50","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1912.11078","article-title":"Predictive biases in natural language processing models: a conceptual framework and overview","author":"Shah","year":"2019","journal-title":"arXiv Preprint"},{"key":"B51","doi-asserted-by":"publisher","first-page":"1029","DOI":"10.1038\/s41562-020-0924-8","article-title":"Cultural influences on word meanings revealed through large-scale semantic alignment","volume":"4","author":"Thompson","year":"2020","journal-title":"Nat. Hum. Behav."},{"key":"B52","first-page":"2579","article-title":"Visualizing data using T-SNE","volume":"9","author":"van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"B53","article-title":"Attention is all you need","volume-title":"31st Conference on Neural Information Processing Systems (NIPS 2017)","author":"Vaswani","year":"2017"},{"key":"B54","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1007\/978-3-319-13734-6_32","article-title":"\u201cIntegrating social media communications into the rapid assessment of sudden onset disasters,\u201d","volume-title":"International Conference on Social Informatics","author":"Vieweg","year":"2014"},{"key":"B55","first-page":"38","article-title":"\u201cTransformers: state-of-the-art natural language processing,\u201d","volume-title":"Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing","author":"Wolf","year":"2020"},{"key":"B56","doi-asserted-by":"crossref","first-page":"87","DOI":"10.18653\/v1\/2020.acl-demos.12","article-title":"\u201cMultilingual universal sentence encoder for semantic retrieval,\u201d","volume-title":"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations","author":"Yang","year":"2020"},{"key":"B57","first-page":"1713","article-title":"\u201cMultihumes: multilingual humanitarian dataset for extractive summarization,\u201d","volume-title":"Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics","author":"Yela-Bello","year":"2021"},{"key":"B58","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1109\/MCI.2018.2840738","article-title":"Recent trends in deep learning based natural language processing","volume":"13","author":"Young","year":"2018","journal-title":"IEEE Comput. Intell. Magaz."}],"container-title":["Frontiers in Big Data"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fdata.2023.1082787\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T05:51:52Z","timestamp":1679637112000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fdata.2023.1082787\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,24]]},"references-count":58,"alternative-id":["10.3389\/fdata.2023.1082787"],"URL":"https:\/\/doi.org\/10.3389\/fdata.2023.1082787","relation":{},"ISSN":["2624-909X"],"issn-type":[{"value":"2624-909X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,24]]},"article-number":"1082787"}}