{"id":"https://openalex.org/W7161802953","doi":"https://doi.org/10.1145/3795766.3799780","title":"Self-Promotion in LLM Recommendations","display_name":"Self-Promotion in LLM Recommendations","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7161802953","doi":"https://doi.org/10.1145/3795766.3799780"},"language":null,"primary_location":{"id":"doi:10.1145/3795766.3799780","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3795766.3799780","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM Web Science Conference 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3795766.3799780","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136540959","display_name":"Rustom M. Dubash","orcid":"https://orcid.org/0009-0002-8786-7290"},"institutions":[{"id":"https://openalex.org/I155707491","display_name":"Haverford College","ror":"https://ror.org/04fnrxr62","country_code":"US","type":"education","lineage":["https://openalex.org/I155707491"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rustom M. Dubash","raw_affiliation_strings":["Haverford College, Haverford, Pennsylvania, USA"],"raw_orcid":"https://orcid.org/0009-0002-8786-7290","affiliations":[{"raw_affiliation_string":"Haverford College, Haverford, Pennsylvania, USA","institution_ids":["https://openalex.org/I155707491"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086384189","display_name":"Sorelle A. Friedler","orcid":"https://orcid.org/0000-0001-6023-1597"},"institutions":[{"id":"https://openalex.org/I155707491","display_name":"Haverford College","ror":"https://ror.org/04fnrxr62","country_code":"US","type":"education","lineage":["https://openalex.org/I155707491"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sorelle A. Friedler","raw_affiliation_strings":["Haverford College, Haverford, Pennsylvania, USA"],"raw_orcid":"https://orcid.org/0000-0001-6023-1597","affiliations":[{"raw_affiliation_string":"Haverford College, Haverford, Pennsylvania, USA","institution_ids":["https://openalex.org/I155707491"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I155707491"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55344655,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"310","last_page":"319"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.4383000135421753,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.4383000135421753,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"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":0.21649999916553497,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.1306000053882599,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.7113000154495239},{"id":"https://openalex.org/keywords/audit","display_name":"Audit","score":0.633400022983551},{"id":"https://openalex.org/keywords/competition","display_name":"Competition (biology)","score":0.4722000062465668},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.46050000190734863},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.43149998784065247}],"concepts":[{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.7113000154495239},{"id":"https://openalex.org/C199521495","wikidata":"https://www.wikidata.org/wiki/Q181487","display_name":"Audit","level":2,"score":0.633400022983551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48730000853538513},{"id":"https://openalex.org/C91306197","wikidata":"https://www.wikidata.org/wiki/Q45767","display_name":"Competition (biology)","level":2,"score":0.4722000062465668},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.46050000190734863},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.43149998784065247},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3675000071525574},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3375999927520752},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.32440000772476196},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.30649998784065247},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C80958533","wikidata":"https://www.wikidata.org/wiki/Q1047174","display_name":"Audit trail","level":3,"score":0.26910001039505005},{"id":"https://openalex.org/C39549134","wikidata":"https://www.wikidata.org/wiki/Q133080","display_name":"Public relations","level":1,"score":0.2685999870300293},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3795766.3799780","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3795766.3799780","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM Web Science Conference 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3795766.3799780","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3795766.3799780","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM Web Science Conference 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2152314154","https://openalex.org/W2161392727","https://openalex.org/W2332851105","https://openalex.org/W2893425640","https://openalex.org/W2941228000","https://openalex.org/W2981869278","https://openalex.org/W2990191328","https://openalex.org/W3095608441","https://openalex.org/W3122748716","https://openalex.org/W3215475614","https://openalex.org/W4288086175","https://openalex.org/W4313559133","https://openalex.org/W4366004080","https://openalex.org/W4380301765","https://openalex.org/W4391974463","https://openalex.org/W4402671190","https://openalex.org/W4403681585","https://openalex.org/W4410081533","https://openalex.org/W4410486474","https://openalex.org/W4410486519"],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2,17,33],"(LLMs)":[3],"are":[4],"used":[5],"across":[6,100],"diverse":[7],"applications,":[8],"creating":[9],"complex":[10],"choices":[11],"for":[12,18,29,48],"users":[13,23],"selecting":[14],"among":[15],"competing":[16],"varying":[19],"use":[20],"cases.":[21],"When":[22],"turn":[24],"to":[25,84,87],"AI":[26,32,142],"systems":[27,144],"themselves":[28],"guidance,":[30],"do":[31],"exhibit":[34],"self-promotional":[35,98],"bias":[36,99],"when":[37],"recommending":[38],"competitors?":[39],"We":[40,79],"conducted":[41],"an":[42],"audit":[43],"of":[44],"three":[45],"major":[46],"providers":[47],"self-promotion":[49],"in":[50],"LLM":[51],"recommendations:":[52],"OpenAI,":[53],"Anthropic,":[54],"and":[55,66,76,138],"Google.":[56],"Using":[57],"prompts":[58],"spanning":[59],"coding,":[60],"mathematics,":[61],"scientific":[62],"reasoning,":[63],"general":[64],"knowledge,":[65],"operational":[67],"domains,":[68],"we":[69],"observed":[70],"how":[71],"each":[72],"company":[73],"ranks":[74],"itself":[75],"its":[77],"competitors.":[78],"compare":[80],"the":[81,127],"collected":[82],"rankings":[83],"performance":[85,116],"benchmarks":[86],"separate":[88],"legitimate":[89],"benchmark-based":[90],"suggestions":[91],"from":[92],"promotional":[93,129],"bias.":[94],"Our":[95],"analysis":[96,120],"reveals":[97],"all":[101],"providers.":[102],"Models":[103],"consistently":[104],"rank":[105],"their":[106,114],"own":[107],"companies\u2019":[108],"products":[109],"0.2":[110],"positions":[111],"higher":[112],"than":[113],"benchmark":[115],"would":[117],"justify.":[118],"Vendor-specific":[119],"shows":[121],"substantial":[122],"variation,":[123],"with":[124],"OpenAI":[125],"exhibiting":[126],"strongest":[128],"tendencies.":[130],"These":[131],"findings":[132],"raise":[133],"important":[134],"questions":[135],"about":[136],"transparency":[137],"fair":[139],"competition":[140],"as":[141],"recommendation":[143],"increasingly":[145],"influence":[146],"technology":[147],"adoption":[148],"decisions.":[149]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-05-21T00:00:00"}
