{"id":"https://openalex.org/W7133359562","doi":"https://doi.org/10.48550/arxiv.2603.01220","title":"Generative AI & Fictionality: How Novels Power Large Language Models","display_name":"Generative AI & Fictionality: How Novels Power Large Language Models","publication_year":2026,"publication_date":"2026-03-01","ids":{"openalex":"https://openalex.org/W7133359562","doi":"https://doi.org/10.48550/arxiv.2603.01220"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01220","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01220","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.01220","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045615435","display_name":"Edwin Roland","orcid":"https://orcid.org/0009-0008-3869-1886"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Roland, Edwin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127963424","display_name":"Richard Jean So","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"So, Richard Jean","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5045615435"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.25920000672340393,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.25920000672340393,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.13539999723434448,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12377","display_name":"Digital Humanities and Scholarship","score":0.09380000084638596,"subfield":{"id":"https://openalex.org/subfields/1208","display_name":"Literature and Literary Theory"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.8176000118255615},{"id":"https://openalex.org/keywords/affordance","display_name":"Affordance","score":0.6891999840736389},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.652400016784668},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5641999840736389},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.3199999928474426}],"concepts":[{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.8176000118255615},{"id":"https://openalex.org/C194995250","wikidata":"https://www.wikidata.org/wiki/Q531136","display_name":"Affordance","level":2,"score":0.6891999840736389},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.652400016784668},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5641999840736389},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5223000049591064},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45100000500679016},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.39399999380111694},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.3935000002384186},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.36390000581741333},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.3124000132083893},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.27730000019073486},{"id":"https://openalex.org/C195818886","wikidata":"https://www.wikidata.org/wiki/Q5421724","display_name":"Expressive power","level":2,"score":0.26089999079704285}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01220","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01220","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.01220","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01220","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.8733980059623718,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Generative":[0],"models,":[1,58],"like":[2],"the":[3,30,39,50,65,82,92,115],"one":[4],"in":[5,67],"ChatGPT,":[6],"are":[7,15,99],"powered":[8],"by":[9,182],"their":[10],"training":[11,205],"data.":[12,206],"The":[13],"models":[14],"simply":[16],"next-word":[17],"predictors,":[18],"based":[19],"on":[20],"patterns":[21],"learned":[22],"from":[23],"vast":[24],"amounts":[25],"of":[26,33,47,76,94,106,132,139,146,161,170,190,194],"pre-existing":[27],"text.":[28],"Since":[29,114],"first":[31],"generation":[32],"GPT,":[34],"it":[35],"is":[36,60,69,179],"striking":[37],"that":[38,64,154,175],"most":[40],"popular":[41],"datasets":[42],"have":[43,126],"included":[44],"substantial":[45],"collections":[46],"novels.":[48],"For":[49],"engineers":[51],"and":[52,78,112,123,129,141,159,168,185],"research":[53],"scientists":[54],"who":[55],"build":[56],"these":[57],"there":[59],"a":[61,137,200],"common":[62],"belief":[63,83],"language":[66],"fiction":[68,90,134],"rich":[70],"enough":[71],"to":[72,103],"cover":[73],"all":[74],"manner":[75],"social":[77,171],"communicative":[79],"phenomena,":[80],"yet":[81],"has":[84],"gone":[85],"mostly":[86],"unexamined.":[87],"How":[88],"does":[89],"shape":[91],"outputs":[93],"generative":[95,183],"AI?":[96],"Specifically,":[97],"what":[98],"novels'":[100],"effects":[101],"relative":[102],"other":[104],"forms":[105,169],"text,":[107],"such":[108,119],"as":[109,120,136],"newspapers,":[110],"Reddit,":[111],"Wikipedia?":[113],"1970s,":[116],"literature":[117],"scholars":[118],"Catherine":[121],"Gallagher":[122],"James":[124],"Phelan":[125],"developed":[127],"robust":[128],"insightful":[130],"accounts":[131],"how":[133],"operates":[135],"form":[138],"discourse":[140],"language.":[142],"Through":[143],"our":[144],"study":[145],"an":[147],"influential":[148],"open-source":[149],"model":[150],"(BERT),":[151],"we":[152],"find":[153],"LLMs":[155],"leverage":[156],"familiar":[157],"attributes":[158],"affordances":[160],"fiction,":[162],"while":[163],"also":[164],"fomenting":[165],"new":[166],"qualities":[167],"response.":[172],"We":[173],"argue":[174],"if":[176],"contemporary":[177],"culture":[178],"increasingly":[180],"shaped":[181],"AI":[184],"machine":[186],"learning,":[187],"any":[188],"analysis":[189],"today's":[191],"various":[192],"modes":[193],"cultural":[195],"production":[196],"must":[197],"account":[198],"for":[199],"relatively":[201],"novel":[202],"dimension:":[203],"computational":[204]},"counts_by_year":[],"updated_date":"2026-03-04T07:09:34.246503","created_date":"2026-03-04T00:00:00"}