{"id":1416,"date":"2020-11-11T12:47:15","date_gmt":"2020-11-11T17:47:15","guid":{"rendered":"https:\/\/www.yorku.ca\/dighr\/project\/improving-humanitarian-needs-assessments-through-natural-language-processing\/"},"modified":"2023-09-28T20:58:05","modified_gmt":"2023-09-29T00:58:05","slug":"improving-humanitarian-needs-assessments-through-natural-language-processing","status":"publish","type":"project","link":"https:\/\/www.yorku.ca\/dighr\/project\/improving-humanitarian-needs-assessments-through-natural-language-processing\/","title":{"rendered":"Improving Humanitarian Needs Assessments through Natural Language Processing"},"content":{"rendered":"

An effective response to humanitarian crises relies on detailed information about the needs of the affected population.<\/p>\n

Current approaches to assessing humanitarian needs through surveys often require interviewers to convert complex, open-ended responses into simplified categorical data. More nuanced insights require the use of qualitative methods, but proper transcription and manual coding are hard to conduct rapidly and at scale during a crisis. As a result, the amount and usefulness of qualitative information to inform humanitarian assistance are severely limited.<\/p>\n

Natural language processing (NLP), a form of artificial intelligence, provides potentially far-reaching new opportunities to capture qualitative data from voice responses and analyze it for relevant content to better inform humanitarian assistance decisions.<\/p>\n

This project, launched in 2018, consists of two main activities:<\/p>\n

    \n
  1. Design a pilot system using NLP to transcribe, translate, and analyze large sets of qualitative responses to a population-based humanitarian need assessment survey with a view to improving the quality and effectiveness of humanitarian assistance.<\/li>\n
  2. Anticipate the ethical challenges of introducing this new technology and other automated decision systems to the humanitarian context\u2014 and create a framework to reduce and mitigate these new risks.<\/li>\n<\/ol>\n
    \n

    Background Literature<\/h2>\n

    Needs Assessment Handbook<\/i>, United Nations High Commissioner for Refugees<\/a>
    \n    Humanitarian Needs Assessment: The Good Enough Guide<\/i>, ACAPS<\/a>
    \n    Needs Assessment and Analysis<\/i>, United Nations Office for the Coordination of Humanitarian Affairs<\/a><\/p>\n

    \n

    Project Team<\/h2>\n

    Tino Kreutzer, PhD Candidate, School of Health Policy and Management
    \nJames Orbinski, Director, Dahdaleh Institute for Global Health Research
    \n    Lora Appel<\/a>, Postdoctoral Research Fellow, OpenLab
    \n    Aijun An<\/a>, Professor, Department of Electrical Engineering and Computer Science, ¿ì²¥ÊÓƵ
    \n    Muath Alzghool<\/a>, Postdoctoral Fellow, ¿ì²¥ÊÓƵ<\/p>\n","protected":false},"author":257,"featured_media":0,"parent":0,"menu_order":0,"template":"","format":"standard","categories":[20,38],"research-theme":[18],"stage":[45],"relationship":[63],"class_list":["post-1416","project","type-project","status-publish","format-standard","hentry","category-project","category-research","research-theme-humanitarianism","stage-concluded","relationship-internal"],"yoast_head":"\nImproving Humanitarian Needs Assessments through Natural Language Processing - Dahdaleh Institute for Global Health Research<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.yorku.ca\/dighr\/project\/improving-humanitarian-needs-assessments-through-natural-language-processing\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Improving Humanitarian Needs Assessments through Natural Language Processing - Dahdaleh Institute for Global Health Research\" \/>\n<meta property=\"og:description\" content=\"An effective response to humanitarian crises relies on detailed information about the needs of the affected population. 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