{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T02:31:34Z","timestamp":1785378694471,"version":"3.55.0"},"reference-count":95,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,11,23]],"date-time":"2023-11-23T00:00:00Z","timestamp":1700697600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100009980","name":"Old Dominion University","doi-asserted-by":"publisher","award":["300916-010"],"award-info":[{"award-number":["300916-010"]}],"id":[{"id":"10.13039\/100009980","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent-based models and simulations consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Simulated agents generate large volumes of data and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents\u2019 perspectives on key life events by providing natural language narratives. However, these narratives should be factual, transparent, and reproducible. Therefore, we present a structured narrative prompt for sending queries to LLMs, we experiment with the narrative generation process using OpenAI\u2019s ChatGPT, and we assess statistically significant differences across 11 Positive and Negative Affect Schedule (PANAS) sentiment levels between the generated narratives and real tweets using chi-squared tests and Fisher\u2019s exact tests. The narrative prompt structure effectively yields narratives with the desired components from ChatGPT. In four out of forty-four categories, ChatGPT generated narratives which have sentiment scores that were not discernibly different, in terms of statistical significance (alpha level \u03b1=0.05), from the sentiment expressed in real tweets. Three outcomes are provided: (1) a list of benefits and challenges for LLMs in narrative generation; (2) a structured prompt for requesting narratives of an LLM chatbot based on simulated agents\u2019 information; (3) an assessment of statistical significance in the sentiment prevalence of the generated narratives compared to real tweets. This indicates significant promise in the utilization of LLMs for helping to connect a simulated agent\u2019s experiences with real people.<\/jats:p>","DOI":"10.3390\/fi15120375","type":"journal-article","created":{"date-parts":[[2023,11,23]],"date-time":"2023-11-23T11:31:25Z","timestamp":1700739085000},"page":"375","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["A Structured Narrative Prompt for Prompting Narratives from Large Language Models: Sentiment Assessment of ChatGPT-Generated Narratives and Real Tweets"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4830-7488","authenticated-orcid":false,"given":"Christopher J.","family":"Lynch","sequence":"first","affiliation":[{"name":"Virginia, Modeling, Analysis, and Simulation Center, Old Dominion University, 1030 University Blvd., Suffolk, VA 23435, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7938-2704","authenticated-orcid":false,"given":"Erik J.","family":"Jensen","sequence":"additional","affiliation":[{"name":"Computational Modeling and Simulation Engineering Department, Old Dominion University, Norfolk, VA 23508, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9079-0947","authenticated-orcid":false,"given":"Virginia","family":"Zamponi","sequence":"additional","affiliation":[{"name":"Virginia, Modeling, Analysis, and Simulation Center, Old Dominion University, 1030 University Blvd., Suffolk, VA 23435, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7980-640X","authenticated-orcid":false,"given":"Kevin","family":"O\u2019Brien","sequence":"additional","affiliation":[{"name":"Virginia, Modeling, Analysis, and Simulation Center, Old Dominion University, 1030 University Blvd., Suffolk, VA 23435, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7694-7845","authenticated-orcid":false,"given":"Erika","family":"Frydenlund","sequence":"additional","affiliation":[{"name":"Virginia, Modeling, Analysis, and Simulation Center, Old Dominion University, 1030 University Blvd., Suffolk, VA 23435, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4065-6146","authenticated-orcid":false,"given":"Ross","family":"Gore","sequence":"additional","affiliation":[{"name":"Virginia, Modeling, Analysis, and Simulation Center, Old Dominion University, 1030 University Blvd., Suffolk, VA 23435, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,23]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"\u201cWe\u2019ve been researched to death\u201d: Exploring the research experiences of urban Indigenous Peoples in Vancouver, Canada","volume":"9","author":"Goodman","year":"2018","journal-title":"Int. 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