{"id":"https://openalex.org/W4387427381","doi":"https://doi.org/10.48550/arxiv.2310.02766","title":"Likelihood-Based Methods Improve Parameter Estimation in Opinion Dynamics Models","display_name":"Likelihood-Based Methods Improve Parameter Estimation in Opinion Dynamics Models","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4387427381","doi":"https://doi.org/10.48550/arxiv.2310.02766"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2310.02766","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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2310.02766","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111052949","display_name":"Jacopo Lenti","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lenti, Jacopo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002012048","display_name":"Corrado Monti","orcid":"https://orcid.org/0000-0001-6846-5718"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Monti, Corrado","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5041680508","display_name":"Gianmarco De Francisci Morales","orcid":"https://orcid.org/0000-0002-2415-494X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Morales, Gianmarco De Francisci","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"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":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":67},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9997,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9997,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9885,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9421,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.46415174},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.4604993}],"concepts":[{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.73282605},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6751003},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6729392},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5289514},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.5016885},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.4847088},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.46415174},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.4604993},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.4460771},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.44056773},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.42771044},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.4271496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42034954},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4133983},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40460187},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3906704},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34942},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.266661},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24419966},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19811353},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2310.02766","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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.02766","pdf_url":"http://arxiv.org/pdf/2310.02766","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2310.02766","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2310.02766","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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4322716735","https://openalex.org/W353185590","https://openalex.org/W3121212717","https://openalex.org/W2964321162","https://openalex.org/W2963987720","https://openalex.org/W2898901530","https://openalex.org/W2750968126","https://openalex.org/W2616125534","https://openalex.org/W2160216316","https://openalex.org/W2106257677"],"abstract_inverted_index":{"We":[0,66,79,112],"show":[1,161,198],"that":[2,35,52,144,164,199],"a":[3,31,49,62,140,146],"maximum":[4,189,201],"likelihood":[5,50,190,202],"approach":[6],"for":[7,122],"parameter":[8],"estimation":[9,191],"in":[10,28,61,177],"agent-based":[11],"models":[12,159,176],"(ABMs)":[13],"of":[14,30,33,76,86,109],"opinion":[15,77],"dynamics":[16],"outperforms":[17],"the":[18,25,41,54,58,72,110,124,127,131,137,153,162,168,173,200],"typical":[19],"simulation-based":[20],"approach.":[21],"Simulation-based":[22],"approaches":[23,47,70],"simulate":[24],"model":[26,75,125,138],"repeatedly":[27],"search":[29],"set":[32],"parameters":[34,56],"generates":[36],"data":[37,60,91,148],"similar":[38],"enough":[39],"to":[40,57,126,206,213],"observed":[42,59,95,101,104,116],"one.":[43],"In":[44],"contrast,":[45],"likelihood-based":[46,132],"derive":[48],"function":[51],"connects":[53],"unknown":[55],"statistically":[63],"principled":[64],"way.":[65],"compare":[67],"these":[68],"two":[69],"on":[71,82,90],"well-known":[73],"bounded-confidence":[74],"dynamics.":[78],"do":[80],"so":[81],"three":[83,154],"realistic":[84],"scenarios":[85,155],"increasing":[87],"complexity":[88],"depending":[89],"availability:":[92],"(i)":[93],"fully":[94],"opinions":[96],"and":[97,117,160,187,210],"interactions,":[98,102],"(ii)":[99],"partially":[100],"(iii)":[103],"interactions":[105],"with":[106],"noisy":[107],"proxies":[108],"opinions.":[111],"highlight":[113],"how":[114],"identifying":[115],"latent":[118],"variables":[119],"is":[120],"fundamental":[121],"connecting":[123],"data.":[128],"To":[129],"realize":[130],"approach,":[133],"we":[134,151,171],"first":[135],"cast":[136],"into":[139,166],"probabilistic":[141,157,175],"generative":[142],"guise":[143],"supports":[145],"proper":[147],"likelihood.":[149],"Then,":[150],"describe":[152],"via":[156,192],"graphical":[158],"nuances":[163],"go":[165],"translating":[167],"model.":[169],"Finally,":[170],"implement":[172],"resulting":[174],"an":[178],"automatic":[179],"differentiation":[180],"framework":[181],"(PyTorch).":[182],"This":[183],"step":[184],"enables":[185],"easy":[186],"efficient":[188],"gradient":[193],"descent.":[194],"Our":[195],"experimental":[196],"results":[197],"estimates":[203],"are":[204],"up":[205,212],"4x":[207],"more":[208],"accurate":[209],"require":[211],"200x":[214],"less":[215],"computational":[216],"time.":[217]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4387427381","counts_by_year":[],"updated_date":"2025-01-04T15:06:05.996999","created_date":"2023-10-08"}