{"id":"https://openalex.org/W7154971770","doi":"https://doi.org/10.48550/arxiv.2604.15937","title":"Polarization by Default: Auditing Recommendation Bias in LLM-Based Content Curation","display_name":"Polarization by Default: Auditing Recommendation Bias in LLM-Based Content Curation","publication_year":2026,"publication_date":"2026-04-17","ids":{"openalex":"https://openalex.org/W7154971770","doi":"https://doi.org/10.48550/arxiv.2604.15937"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.15937","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15937","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.15937","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134030744","display_name":"Nicol\u00f2 Pagan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pagan, Nicol\u00f2","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031713577","display_name":"Christopher Barrie","orcid":"https://orcid.org/0000-0002-9156-990X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barrie, Christopher","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134081139","display_name":"Chris Andrew Bail","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bail, Chris Andrew","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5047808749","display_name":"Petter T\u00f6rnberg","orcid":"https://orcid.org/0000-0001-8722-8646"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"T\u00f6rnberg, Petter","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.15289999544620514,"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"}},"topics":[{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.15289999544620514,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.1412999927997589,"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/T12027","display_name":"Social Media in Health Education","score":0.10000000149011612,"subfield":{"id":"https://openalex.org/subfields/3306","display_name":"Health"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/audit","display_name":"Audit","score":0.6608999967575073},{"id":"https://openalex.org/keywords/demographics","display_name":"Demographics","score":0.6014999747276306},{"id":"https://openalex.org/keywords/polarization","display_name":"Polarization (electrochemistry)","score":0.559499979019165},{"id":"https://openalex.org/keywords/debiasing","display_name":"Debiasing","score":0.48500001430511475},{"id":"https://openalex.org/keywords/selection-bias","display_name":"Selection bias","score":0.4652999937534332},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.43700000643730164},{"id":"https://openalex.org/keywords/confirmation-bias","display_name":"Confirmation bias","score":0.39649999141693115}],"concepts":[{"id":"https://openalex.org/C199521495","wikidata":"https://www.wikidata.org/wiki/Q181487","display_name":"Audit","level":2,"score":0.6608999967575073},{"id":"https://openalex.org/C2780084366","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demographics","level":2,"score":0.6014999747276306},{"id":"https://openalex.org/C205049153","wikidata":"https://www.wikidata.org/wiki/Q2698605","display_name":"Polarization (electrochemistry)","level":2,"score":0.559499979019165},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5426999926567078},{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.48500001430511475},{"id":"https://openalex.org/C40423286","wikidata":"https://www.wikidata.org/wiki/Q284172","display_name":"Selection bias","level":2,"score":0.4652999937534332},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.45399999618530273},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.43700000643730164},{"id":"https://openalex.org/C79585631","wikidata":"https://www.wikidata.org/wiki/Q431498","display_name":"Confirmation bias","level":2,"score":0.39649999141693115},{"id":"https://openalex.org/C126349790","wikidata":"https://www.wikidata.org/wiki/Q905036","display_name":"Computational sociology","level":2,"score":0.36329999566078186},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.35910001397132874},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.3495999872684479},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3253999948501587},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.28859999775886536},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.27630001306533813},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C73301696","wikidata":"https://www.wikidata.org/wiki/Q5469984","display_name":"Formalism (music)","level":3,"score":0.2720000147819519},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2696000039577484},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.2662000060081482},{"id":"https://openalex.org/C116537","wikidata":"https://www.wikidata.org/wiki/Q2169973","display_name":"Service provider","level":3,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.15937","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15937","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.15937","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15937","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"are":[4,29,129,183],"increasingly":[5],"deployed":[6],"to":[7],"curate":[8],"and":[9,16,33,35,69,104,123,126,147,196],"rank":[10],"human-created":[11],"content,":[12],"yet":[13],"the":[14,140,157,177,190,194],"nature":[15],"structure":[17],"of":[18,88],"their":[19],"biases":[20,28,52,98,128],"in":[21,101,152,193],"these":[22],"tasks":[23],"remains":[24],"poorly":[25],"understood:":[26],"which":[27,36],"robust":[30],"across":[31,53,91,112,144,201],"providers":[32,57],"platforms,":[34],"can":[37,167],"be":[38,168],"mitigated":[39],"through":[40],"prompt":[41],"design.":[42],"We":[43],"present":[44],"a":[45,118],"controlled":[46],"simulation":[47],"study":[48],"mapping":[49],"content":[50],"selection":[51],"three":[54],"major":[55],"LLM":[56],"(OpenAI,":[58],"Anthropic,":[59],"Google)":[60],"on":[61],"real":[62],"social":[63],"media":[64],"datasets":[65],"from":[66,86,170],"Twitter/X,":[67,163],"Bluesky,":[68],"Reddit,":[70],"using":[71],"six":[72],"prompting":[73],"strategies":[74],"(\\textit{general},":[75],"\\textit{popular},":[76],"\\textit{engaging},":[77],"\\textit{informative},":[78],"\\textit{controversial},":[79],"\\textit{neutral}).":[80],"Through":[81],"540,000":[82],"simulated":[83],"top-10":[84],"selections":[85],"pools":[87],"100":[89],"posts":[90],"54":[92],"experimental":[93],"conditions,":[94],"we":[95],"find":[96],"that":[97],"differ":[99],"substantially":[100],"how":[102,105],"structural":[103],"prompt-sensitive":[106],"they":[107],"are.":[108],"Polarization":[109],"is":[110,176],"amplified":[111],"all":[113],"configurations,":[114],"toxicity":[115,153],"handling":[116],"shows":[117,139,156],"strong":[119],"inversion":[120],"between":[121],"engagement-":[122],"information-focused":[124],"prompts,":[125],"sentiment":[127,160],"predominantly":[130],"negative.":[131],"Provider":[132],"comparisons":[133],"reveal":[134],"distinct":[135],"trade-offs:":[136],"GPT-4o":[137],"Mini":[138],"most":[141],"consistent":[142],"behavior":[143],"prompts;":[145],"Claude":[146],"Gemini":[148,155],"exhibit":[149],"high":[150],"adaptivity":[151],"handling;":[154],"strongest":[158],"negative":[159],"preference.":[161],"On":[162],"where":[164],"author":[165],"demographics":[166],"inferred":[169],"profile":[171],"bios,":[172],"political":[173],"leaning":[174],"bias":[175],"clearest":[178],"demographic":[179],"signal:":[180],"left-leaning":[181],"authors":[182,188],"systematically":[184],"over-represented":[185],"despite":[186],"right-leaning":[187],"forming":[189],"pool":[191],"plurality":[192],"dataset,":[195],"this":[197],"pattern":[198],"largely":[199],"persists":[200],"prompts.":[202]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-21T00:00:00"}