Classifying Peace in Global Media Using RAG and Intergroup Reciprocity
K. Lian (1), L. S. Liebovitch (1), M. Wild (1), H. West (1), P. T., Coleman (1), F. Chen (2), E. Kimani (2), K. Sieck (2) ((1) Columbia, University, (2) Toyota Research Institute)
TL;DR
This paper introduces a new method combining Retrieval Augmented Generation and intergroup reciprocity concepts to analyze peace-related content in global media, offering more precise insights into peace dynamics.
Contribution
It refines PIR/NIR definitions and applies RAG to media analysis, advancing understanding of intergroup relations and peace indicators in media content.
Findings
Enhanced accuracy in identifying peace insights in media
New definitions improve analysis of intergroup relations
Method reveals dynamics affecting peace at national levels
Abstract
This paper presents a novel approach to identifying insights of peace in global media using a Retrieval Augmented Generation (RAG) model and concepts of Positive and Negative Intergroup Reciprocity (PIR/NIR). By refining the definitions of PIR and NIR, we offer a more accurate and meaningful analysis of intergroup relations as represented in media articles. Our methodology provides insights into the dynamics that contribute to or detract from peace at a national level.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsInnovative Teaching Methodologies in Social Sciences