{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:36:18Z","timestamp":1761176178512,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>This paper presents a computational framework for simulating the evolution of text by modeling textual units as memes \u2013 replicable cultural information analogous to genes. Memes occupy nodes in a graph, where edges represent pathways of interaction. Memes propagate probabilistically along these edges based on weights. Following propagation, a fitness function evaluates each meme, guiding a selection process based on configurable criteria. This selection determines whether Large Language Models (LLMs) then introduce variation by mutating or merging memes, adapting content during transmission. Through iterative cycles of propagation, selection, and variation, the system models how memes evolve, spread, and adapt within networked populations. Source code is available at https:\/\/github.com\/karlo-babic\/graph-meme-pool\/.<\/jats:p>","DOI":"10.3233\/faia251014","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:48:55Z","timestamp":1761126535000},"source":"Crossref","is-referenced-by-count":0,"title":["Selection in the Meme Pool: Graph-Based Evolution of Textual Content"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6343-0938","authenticated-orcid":false,"given":"Karlo","family":"Babi\u0107","sequence":"first","affiliation":[{"name":"University of Rijeka, Faculty of Informatics and Digital Technologies"},{"name":"University of Rijeka, Center for Artificial Intelligence and Cybersecurity"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251014","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:48:56Z","timestamp":1761126536000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251014"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251014","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}