{"id":22816,"date":"2024-03-01T10:03:55","date_gmt":"2024-03-01T10:03:55","guid":{"rendered":"https:\/\/peacerep.org\/?post_type=publication&#038;p=22816"},"modified":"2025-01-03T11:13:46","modified_gmt":"2025-01-03T11:13:46","slug":"extracting-named-actors-from-text","status":"publish","type":"publication","link":"https:\/\/gentest.cahss.ed.ac.uk\/dev-peacerep\/publication\/extracting-named-actors-from-text\/","title":{"rendered":"Extracting Named Actors from Text: Using Named Entity Recognition (NER) in Peace and Conflict Studies"},"content":{"rendered":"<p><strong>Author:<\/strong> Niamh Henry<\/p>\n<p>This report explores the potential role of Named Entity Recognition (NER) in peace and conflict studies, drawing insights from PeaceRep\u2019s use of the technology to extract signatory organisations from a large-scale database containing peace agreements \u2013 the PA-X Peace Agreements Database. PeaceRep\u2019s successful application of NER in extracting signatory data from peace agreement texts provides an example of how to navigate complex textual data relevant to ending conflict, in a time where we increasingly require data as evidence for decision making. As text remains the primary medium in this domain, NER emerges as a crucial tool in identifying, extracting, and structuring key data, facilitating streamlined research and information extraction.<\/p>\n<p>Highlighting NER fundamentals and methodological approaches, this report advocates for transparent artificial intelligence, human oversight, and a functional approach tailored to peace and conflict studies. Accompanied by practical demonstrations in Python Jupyter Notebooks, the report showcases NER\u2019s applications\u2014from document summarisation to geospatial and temporal analysis. Ultimately, it emphasises NER\u2019s potential in deciphering complex textual data while emphasising, and recommending, the need for nuanced approaches that balance NER\u2019s strengths with its limitations in this critical field.<\/p>\n<h4>Peace Analytics Series<\/h4>\n<p>PeaceRep\u2019s\u00a0<a href=\"https:\/\/peacerep.org\/research\/peace-analytics-series\/\" target=\"_blank\" rel=\"noopener\">Peace Analytics Series<\/a>\u00a0features the research methodology underlying the PeaceTech innovations of the PeaceRep programme.<\/p>\n<p>The series includes: data scoping research; \u2018how to\u2019 discussions relating to particular challenges in the field of visualisations and geocoding; and other proof-of-concept tech-based innovations, such as the use of natural language processing. It is intended to present the methodologies and decisions behind our PeaceTech digital research, to make it transparent, and to contribute to establishing a new research digital infrastructure in the field of peace and conflict studies, by supporting others to reuse and repurpose our methodologies and findings.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This report explores the potential role of Named Entity Recognition (NER) in peace and conflict studies, drawing insights from PeaceRep&#8217;s use of the technology.<\/p>\n","protected":false},"author":166,"featured_media":22817,"template":"","meta":{"_acf_changed":false,"_FSMCFIC_featured_image_caption":"","_FSMCFIC_featured_image_nocaption":"","_FSMCFIC_featured_image_hide":""},"categories":[1838,235],"tags":[658],"authors":[2051],"class_list":["post-22816","publication","type-publication","status-publish","has-post-thumbnail","hentry","category-peacetech","category-publication","tag-publication","countries-global","authors-henry","themes-peacetech"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - 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