{"id":"https://openalex.org/W3214187913","doi":"https://doi.org/10.1145/3643562.3673895","title":"Full Characterization of Adaptively Strong Majority Voting in Crowdsourcing","display_name":"Full Characterization of Adaptively Strong Majority Voting in Crowdsourcing","publication_year":2024,"publication_date":"2024-06-27","ids":{"openalex":"https://openalex.org/W3214187913","doi":"https://doi.org/10.1145/3643562.3673895","mag":"3214187913"},"language":"en","primary_location":{"id":"doi:10.1145/3643562.3673895","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3643562.3673895","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Collective Intelligence Conference","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061155071","display_name":"Margarita Boyarskaya","orcid":"https://orcid.org/0000-0002-8181-6030"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Margarita Boyarskaya","raw_affiliation_strings":["Technology, Operations, and Statistics, NYU Stern, USA"],"raw_orcid":"https://orcid.org/0000-0002-8181-6030","affiliations":[{"raw_affiliation_string":"Technology, Operations, and Statistics, NYU Stern, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010731709","display_name":"Panagiotis G. Ipeirotis","orcid":"https://orcid.org/0000-0002-2966-7402"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Panos Ipeirotis","raw_affiliation_strings":["Technology, Operations, and Statistics, NYU Stern, USA","New York University**"],"raw_orcid":"https://orcid.org/0000-0002-2966-7402","affiliations":[{"raw_affiliation_string":"Technology, Operations, and Statistics, NYU Stern, USA","institution_ids":[]},{"raw_affiliation_string":"New York University**","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3593,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.65457665,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"41","last_page":"62"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10991","display_name":"Game Theory and Voting Systems","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11182","display_name":"Auction Theory and Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.8443779349327087},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.843460202217102},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6642864346504211},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.5963211059570312},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4751589000225067},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4638654589653015},{"id":"https://openalex.org/keywords/payment","display_name":"Payment","score":0.4541782736778259},{"id":"https://openalex.org/keywords/equivalence","display_name":"Equivalence (formal languages)","score":0.45382627844810486},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.446767657995224},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.44593220949172974},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.421028196811676},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41944846510887146},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.36275577545166016},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3413918614387512},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3068709969520569},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2798369526863098},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.197885662317276},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0990469753742218},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.08307155966758728}],"concepts":[{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.8443779349327087},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.843460202217102},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6642864346504211},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.5963211059570312},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4751589000225067},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4638654589653015},{"id":"https://openalex.org/C145097563","wikidata":"https://www.wikidata.org/wiki/Q1148747","display_name":"Payment","level":2,"score":0.4541782736778259},{"id":"https://openalex.org/C2780069185","wikidata":"https://www.wikidata.org/wiki/Q7977945","display_name":"Equivalence (formal languages)","level":2,"score":0.45382627844810486},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.446767657995224},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.44593220949172974},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.421028196811676},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41944846510887146},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.36275577545166016},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3413918614387512},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3068709969520569},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2798369526863098},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.197885662317276},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0990469753742218},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.08307155966758728},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3643562.3673895","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3643562.3673895","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Collective Intelligence Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6200000047683716,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W59714529","https://openalex.org/W108763474","https://openalex.org/W118259468","https://openalex.org/W235137809","https://openalex.org/W335022172","https://openalex.org/W1586124026","https://openalex.org/W1598142793","https://openalex.org/W1978187524","https://openalex.org/W1979483312","https://openalex.org/W1985095406","https://openalex.org/W2032901676","https://openalex.org/W2064975723","https://openalex.org/W2078429476","https://openalex.org/W2091699648","https://openalex.org/W2098805624","https://openalex.org/W2107394329","https://openalex.org/W2117470435","https://openalex.org/W2117539524","https://openalex.org/W2120396827","https://openalex.org/W2122067387","https://openalex.org/W2127172185","https://openalex.org/W2131141188","https://openalex.org/W2148712149","https://openalex.org/W2149273804","https://openalex.org/W2163522723","https://openalex.org/W2221430606","https://openalex.org/W2262972580","https://openalex.org/W2277195237","https://openalex.org/W2289052659","https://openalex.org/W2410382620","https://openalex.org/W2588401322","https://openalex.org/W2616605651","https://openalex.org/W2738227981","https://openalex.org/W2799406519","https://openalex.org/W2807634467","https://openalex.org/W2911280963","https://openalex.org/W2913841425","https://openalex.org/W2914783728","https://openalex.org/W2915480215","https://openalex.org/W2964064650","https://openalex.org/W2964305490","https://openalex.org/W2974168418","https://openalex.org/W3098243577","https://openalex.org/W3111892720","https://openalex.org/W4212957416","https://openalex.org/W4230792291","https://openalex.org/W4245848455","https://openalex.org/W4254560189"],"related_works":["https://openalex.org/W2039876276","https://openalex.org/W2605569989","https://openalex.org/W3121841074","https://openalex.org/W2055572829","https://openalex.org/W2109094787","https://openalex.org/W3036613766","https://openalex.org/W1894159578","https://openalex.org/W2807400035","https://openalex.org/W4297796115","https://openalex.org/W3125086856"],"abstract_inverted_index":{"In":[0],"crowdsourcing,":[1],"quality":[2,87,121],"control":[3],"is":[4,30,46,50],"commonly":[5],"achieved":[6],"by":[7],"having":[8],"workers":[9,45,128],"examine":[10],"items":[11,152],"and":[12,105,158],"vote":[13,103,171],"on":[14],"their":[15],"correctness.":[16],"To":[17],"minimize":[18],"the":[19,70,86,92,100,113,161,174,182],"impact":[20],"of":[21,72,88,95,102,156,163,176,188],"unreliable":[22],"worker":[23],"responses,":[24],"a":[25,38,56,61],"\u03b4":[26,41,115],"-margin":[27],"voting":[28,74,124,140],"process":[29,49,75],"utilized,":[31],"where":[32],"additional":[33],"votes":[34,96],"are":[35],"solicited":[36],"until":[37],"predetermined":[39],"threshold":[40,114],"for":[42,85,98,139],"agreement":[43],"between":[44],"exceeded.":[47],"The":[48,186],"widely":[51],"adopted":[52],"but":[53],"only":[54],"as":[55],"heuristic.":[57],"Our":[58,109,166],"research":[59],"presents":[60],"modeling":[62],"approach":[63],"using":[64,168],"absorbing":[65],"Markov":[66],"chains":[67],"to":[68,119],"analyze":[69],"characteristics":[71],"this":[73],"that":[76,126],"matter":[77],"in":[78,180,195],"crowdsourced":[79,170],"processes.":[80],"We":[81,133],"provide":[82,135],"closed-form":[83],"equations":[84],"resulting":[89],"consensus":[90,183],"vote,":[91],"expected":[93,144],"number":[94],"required":[97],"consensus,":[99],"variance":[101],"requirements,":[104],"other":[106],"distribution":[107],"moments.":[108],"findings":[110],"demonstrate":[111],"how":[112],"can":[116,191],"be":[117,192],"adjusted":[118],"achieve":[120],"equivalence":[122],"across":[123],"processes":[125,141],"employ":[127],"with":[129,142,153],"varying":[130,154],"accuracy":[131,146],"levels.":[132,147],"also":[134],"efficiency-equalizing":[136],"payment":[137],"rates":[138],"different":[143],"response":[145],"Additionally,":[148],"our":[149,177,189],"model":[150,179],"considers":[151],"degrees":[155],"difficulty":[157,162],"uncertainty":[159],"about":[160],"each":[164],"example.":[165],"simulations,":[167],"real-world":[169],"data,":[172],"validate":[173],"effectiveness":[175],"theoretical":[178],"characterizing":[181],"aggregation":[184],"process.":[185],"results":[187],"study":[190],"effectively":[193],"employed":[194],"practical":[196],"crowdsourcing":[197],"applications.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
