{"id":"https://openalex.org/W7160859064","doi":"https://doi.org/10.48550/arxiv.2605.06749","title":"A Statistical Framework for Algorithmic Collective Action with Multiple Collectives","display_name":"A Statistical Framework for Algorithmic Collective Action with Multiple Collectives","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160859064","doi":"https://doi.org/10.48550/arxiv.2605.06749"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.06749","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06749","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.06749","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062501594","display_name":"Claudio Battiloro","orcid":"https://orcid.org/0000-0003-0090-5355"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Battiloro, Claudio","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108590468","display_name":"Pietro Greiner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Greiner, Pietro","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107784108","display_name":"Dario Rancati","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rancati, Dario","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135848127","display_name":"Bret Nestor","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nestor, Bret","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135838633","display_name":"Oumaima Amezgar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Amezgar, Oumaima","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5080486553","display_name":"Francesca Dominici","orcid":"https://orcid.org/0000-0001-5964-0756"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dominici, Francesca","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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.14270000159740448,"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"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.14270000159740448,"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"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.05700000002980232,"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"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.04910000041127205,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/collective-action","display_name":"Collective action","score":0.6908000111579895},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.5037000179290771},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4864000082015991},{"id":"https://openalex.org/keywords/collective-intelligence","display_name":"Collective intelligence","score":0.46219998598098755},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4092000126838684},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.39010000228881836},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3634999990463257}],"concepts":[{"id":"https://openalex.org/C2777932401","wikidata":"https://www.wikidata.org/wiki/Q1471594","display_name":"Collective action","level":3,"score":0.6908000111579895},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6281999945640564},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.5037000179290771},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4864000082015991},{"id":"https://openalex.org/C89057211","wikidata":"https://www.wikidata.org/wiki/Q432197","display_name":"Collective intelligence","level":2,"score":0.46219998598098755},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4092000126838684},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.39010000228881836},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3634999990463257},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30410000681877136},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3001999855041504},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2815000116825104},{"id":"https://openalex.org/C41550386","wikidata":"https://www.wikidata.org/wiki/Q529909","display_name":"Multi-agent system","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C2982736386","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Statistical learning","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C100339178","wikidata":"https://www.wikidata.org/wiki/Q2548752","display_name":"Collective behavior","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.06749","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06749","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.06749","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06749","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":"Preprint"},"sustainable_development_goals":[{"display_name":"Climate action","score":0.8650314807891846,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"learning":[1],"systems":[2],"increasingly":[3],"shape":[4],"everyday":[5],"decisions,":[6],"Algorithmic":[7],"Collective":[8],"Action":[9],"(ACA),":[10],"i.e.,":[11],"users":[12],"coordinating":[13],"changes":[14],"to":[15,18,25],"shared":[16],"data":[17],"steer":[19],"model":[20,30],"behavior,":[21],"offers":[22],"a":[23,104],"complement":[24],"regulator-side":[26],"policy":[27],"and":[28,39,55,121,128,150],"corporate":[29],"design.":[31],"Real-world":[32],"collective":[33,50,67,94,141],"actions":[34],"have":[35],"traditionally":[36],"been":[37],"decentralized":[38],"fragmented":[40],"into":[41],"multiple":[42,82,100],"collectives,":[43,117],"despite":[44],"sharing":[45],"overarching":[46],"objectives,":[47],"with":[48,81,142],"each":[49,140],"differing":[51],"in":[52,96,166],"size,":[53],"strategy,":[54],"actionable":[56],"goals.":[57,133],"However,":[58],"most":[59],"of":[60,115,124,131,146,172],"the":[61,74,86,113,116,119,122,125,129,170],"ACA":[62,80],"literature":[63],"focuses":[64],"on":[65,85,93,112,158],"single":[66],"settings.":[68],"To":[69],"address":[70],"this,":[71],"we":[72,91,153],"propose":[73],"first":[75],"comprehensive":[76],"statistical":[77,110],"framework":[78,157],"for":[79,163],"collectives":[83,101],"acting":[84],"same":[87],"system.":[88],"In":[89],"particular,":[90],"focus":[92],"action":[95],"classification,":[97],"studying":[98],"how":[99],"can":[102],"influence":[103],"classifier's":[105],"behavior.":[106],"We":[107,134],"provide":[108],"quantitative":[109],"bounds":[111,137],"success":[114],"considering":[118],"role":[120],"interplay":[123],"collectives'":[126,148],"sizes":[127,149],"alignment":[130],"their":[132],"make":[135],"such":[136],"computable":[138],"by":[139,161],"only":[143],"partial":[144],"knowledge":[145],"other":[147],"strategies.":[151],"Finally,":[152],"numerically":[154],"illustrate":[155],"our":[156,173],"simulations":[159],"inspired":[160],"interventions":[162],"climate":[164],"adaptation":[165],"smart":[167],"cities,":[168],"demonstrating":[169],"usefulness":[171],"bounds.":[174]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-12T00:00:00"}