{"id":"https://openalex.org/W3135415433","doi":"https://doi.org/10.1145/3490486.3538269","title":"Design and Analysis of Bipartite Experiments Under a Linear Exposure-response Model","display_name":"Design and Analysis of Bipartite Experiments Under a Linear Exposure-response Model","publication_year":2022,"publication_date":"2022-07-12","ids":{"openalex":"https://openalex.org/W3135415433","doi":"https://doi.org/10.1145/3490486.3538269","mag":"3135415433"},"language":"en","primary_location":{"id":"doi:10.1145/3490486.3538269","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3490486.3538269","pdf_url":null,"source":{"id":"https://openalex.org/S4363608973","display_name":"Proceedings of the 23rd ACM Conference on Economics and Computation","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM Conference on Economics and Computation","raw_type":"proceedings-article"},"type":"article","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/A5089136089","display_name":"Christopher Harshaw","orcid":"https://orcid.org/0000-0002-1400-7356"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Christopher Harshaw","raw_affiliation_strings":["University of California, Berkeley, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070232947","display_name":"Fredrik S\u00e4vje","orcid":"https://orcid.org/0000-0003-2544-8250"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fredrik S\u00e4vje","raw_affiliation_strings":["Yale University, New Haven, CT, USA"],"affiliations":[{"raw_affiliation_string":"Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076173304","display_name":"David Eisenstat","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Eisenstat","raw_affiliation_strings":["Google Research, New York City, NY, USA"],"affiliations":[{"raw_affiliation_string":"Google Research, New York City, NY, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075598023","display_name":"Vahab Mirrokni","orcid":"https://orcid.org/0000-0001-6705-5629"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vahab Mirrokni","raw_affiliation_strings":["Google Research, New York City, NY, USA"],"affiliations":[{"raw_affiliation_string":"Google Research, New York City, NY, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013723114","display_name":"Jean Pouget-Abadie","orcid":"https://orcid.org/0000-0003-3729-9547"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jean Pouget-Abadie","raw_affiliation_strings":["Google Research, New York City, NY, USA"],"affiliations":[{"raw_affiliation_string":"Google Research, New York City, NY, USA","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5089136089"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":3.4049,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.93472585,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"606","last_page":"606"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9678999781608582,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.9638527631759644},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5954447388648987},{"id":"https://openalex.org/keywords/discounting","display_name":"Discounting","score":0.5920759439468384},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5425354838371277},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.5320853590965271},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4913124144077301},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.464205801486969},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.39953935146331787},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3671448528766632},{"id":"https://openalex.org/keywords/mathematical-economics","display_name":"Mathematical economics","score":0.21682971715927124},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2124772071838379},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.06536388397216797}],"concepts":[{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.9638527631759644},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5954447388648987},{"id":"https://openalex.org/C6177178","wikidata":"https://www.wikidata.org/wiki/Q10998070","display_name":"Discounting","level":2,"score":0.5920759439468384},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5425354838371277},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.5320853590965271},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4913124144077301},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.464205801486969},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39953935146331787},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3671448528766632},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.21682971715927124},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2124772071838379},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.06536388397216797},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3490486.3538269","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3490486.3538269","pdf_url":null,"source":{"id":"https://openalex.org/S4363608973","display_name":"Proceedings of the 23rd ACM Conference on Economics and Computation","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM Conference on Economics and Computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.47999998927116394}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W76777312","https://openalex.org/W1582351126","https://openalex.org/W1978108654","https://openalex.org/W1990054777","https://openalex.org/W1996564297","https://openalex.org/W2001947543","https://openalex.org/W2012797835","https://openalex.org/W2017732166","https://openalex.org/W2027731328","https://openalex.org/W2048044409","https://openalex.org/W2071489416","https://openalex.org/W2101829497","https://openalex.org/W2110962385","https://openalex.org/W2114389382","https://openalex.org/W2121357720","https://openalex.org/W2132917208","https://openalex.org/W2144459985","https://openalex.org/W2146081992","https://openalex.org/W2148349356","https://openalex.org/W2167595480","https://openalex.org/W2189069876","https://openalex.org/W2189585271","https://openalex.org/W2295665070","https://openalex.org/W2399404755","https://openalex.org/W2463347236","https://openalex.org/W2498075681","https://openalex.org/W2581418816","https://openalex.org/W2608151934","https://openalex.org/W2619368739","https://openalex.org/W2619782566","https://openalex.org/W2796251014","https://openalex.org/W2946387282","https://openalex.org/W2962755348","https://openalex.org/W2963351205","https://openalex.org/W2963409255","https://openalex.org/W2964337893","https://openalex.org/W2966909581","https://openalex.org/W2971142628","https://openalex.org/W3020710313","https://openalex.org/W3040914334","https://openalex.org/W3090901436","https://openalex.org/W3098649723","https://openalex.org/W3106294663","https://openalex.org/W3113367757","https://openalex.org/W3115586144","https://openalex.org/W3122659614","https://openalex.org/W3122863737","https://openalex.org/W3123781182","https://openalex.org/W3125643184","https://openalex.org/W3125904850","https://openalex.org/W3127174137","https://openalex.org/W3131242353","https://openalex.org/W3135804599","https://openalex.org/W3150266318","https://openalex.org/W3150893739"],"related_works":["https://openalex.org/W2371352078","https://openalex.org/W2953461625","https://openalex.org/W2077383796","https://openalex.org/W2080136900","https://openalex.org/W2999799752","https://openalex.org/W2372768926","https://openalex.org/W2054458431","https://openalex.org/W2115167491","https://openalex.org/W2978999882","https://openalex.org/W2567825307"],"abstract_inverted_index":{"A":[0],"bipartite":[1,31,44],"experiment":[2],"consists":[3],"of":[4,7,15,25,61],"one":[5],"set":[6,14],"units":[8,16,26,37],"being":[9],"assigned":[10],"treatments":[11],"and":[12],"another":[13],"for":[17,52],"which":[18],"we":[19],"measure":[20],"outcomes.":[21],"The":[22,43],"two":[23],"sets":[24],"are":[27],"connected":[28],"by":[29],"a":[30],"graph,":[32],"governing":[33],"how":[34],"the":[35,40,59],"treated":[36],"can":[38],"affect":[39],"outcome":[41],"units.":[42],"framework":[45],"naturally":[46],"arises":[47],"in":[48],"marketplace":[49],"experiments":[50],"where,":[51],"example,":[53],"experimenters":[54],"may":[55],"seek":[56],"to":[57],"investigate":[58],"effect":[60],"discounting":[62],"goods":[63],"on":[64],"buyer":[65],"behavior.":[66]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
