{"id":"https://openalex.org/W3148134311","doi":"https://doi.org/10.1109/asonam49781.2020.9381449","title":"Mechanisms of Behavioral Contagion: An Approximate Bayesian Approach","display_name":"Mechanisms of Behavioral Contagion: An Approximate Bayesian Approach","publication_year":2020,"publication_date":"2020-12-07","ids":{"openalex":"https://openalex.org/W3148134311","doi":"https://doi.org/10.1109/asonam49781.2020.9381449","mag":"3148134311"},"language":"en","primary_location":{"id":"doi:10.1109/asonam49781.2020.9381449","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam49781.2020.9381449","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","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/A5038360180","display_name":"Christian C. Luhmann","orcid":"https://orcid.org/0000-0002-9773-1672"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Christian C. Luhmann","raw_affiliation_strings":["Department of Psychology, Institute for Advanced Computational Science, Stony Brook University, Stony Brook, NY"],"affiliations":[{"raw_affiliation_string":"Department of Psychology, Institute for Advanced Computational Science, Stony Brook University, Stony Brook, NY","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055299615","display_name":"Brian Yang","orcid":"https://orcid.org/0000-0001-8784-1459"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Yang","raw_affiliation_strings":["Stony Brook University, Stony Brook, NY"],"affiliations":[{"raw_affiliation_string":"Stony Brook University, Stony Brook, NY","institution_ids":["https://openalex.org/I59553526"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5038360180"],"corresponding_institution_ids":["https://openalex.org/I59553526"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19374168,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"286","issue":null,"first_page":"606","last_page":"610"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9990000128746033,"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/T11031","display_name":"Game Theory and Applications","score":0.9922000169754028,"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/computer-science","display_name":"Computer science","score":0.5989915728569031},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5921169519424438},{"id":"https://openalex.org/keywords/emotional-contagion","display_name":"Emotional contagion","score":0.5612587332725525},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4886325001716614},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.48610520362854004},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.4811207354068756},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.47204670310020447},{"id":"https://openalex.org/keywords/empirical-evidence","display_name":"Empirical evidence","score":0.4583614766597748},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36882075667381287},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3467227518558502},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.2470046877861023},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.22784915566444397},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13178575038909912},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09331238269805908},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.09150204062461853}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5989915728569031},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5921169519424438},{"id":"https://openalex.org/C159237981","wikidata":"https://www.wikidata.org/wiki/Q1498207","display_name":"Emotional contagion","level":2,"score":0.5612587332725525},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4886325001716614},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.48610520362854004},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.4811207354068756},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.47204670310020447},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.4583614766597748},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36882075667381287},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3467227518558502},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.2470046877861023},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.22784915566444397},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13178575038909912},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09331238269805908},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.09150204062461853},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asonam49781.2020.9381449","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam49781.2020.9381449","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G423862433","display_name":null,"funder_award_id":"1456928,1531492","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1556348243","https://openalex.org/W1556758605","https://openalex.org/W2008620264","https://openalex.org/W2061820396","https://openalex.org/W2075395993","https://openalex.org/W2096563449","https://openalex.org/W2108858998","https://openalex.org/W2112090702","https://openalex.org/W2116416291","https://openalex.org/W2129531883","https://openalex.org/W2139812092","https://openalex.org/W2332503218","https://openalex.org/W2550537883","https://openalex.org/W2895152177","https://openalex.org/W3081803702","https://openalex.org/W3103960870","https://openalex.org/W4212942297","https://openalex.org/W6633208645"],"related_works":["https://openalex.org/W976271273","https://openalex.org/W2407375987","https://openalex.org/W3049691116","https://openalex.org/W2505726097","https://openalex.org/W2010643158","https://openalex.org/W4281748496","https://openalex.org/W2106867672","https://openalex.org/W3081214562","https://openalex.org/W4310268968","https://openalex.org/W2950975704"],"abstract_inverted_index":{"Researchers":[0],"have":[1],"proposed":[2],"that":[3,39],"contagion":[4,20],"processes":[5],"govern":[6],"how":[7,63],"information":[8],"and":[9],"behavior":[10],"itself":[11],"spreads":[12],"through":[13],"social":[14],"networks.":[15],"Empirical":[16],"evidence":[17],"for":[18],"such":[19],"often":[21],"makes":[22],"unjustified,":[23],"but":[24],"implicit":[25],"assumptions":[26],"about":[27,46],"the":[28,47],"mechanisms":[29],"underlying":[30,48],"contagion.":[31],"Here,":[32],"we":[33],"present":[34],"an":[35],"approximate":[36],"Bayesian":[37],"method":[38],"uses":[40],"empirical":[41],"data":[42],"to":[43],"draw":[44],"inferences":[45],"mechanisms.":[49],"We":[50],"provide":[51],"initial":[52],"validation":[53],"of":[54],"our":[55],"approach":[56],"in":[57],"three":[58],"simulation":[59],"experiments,":[60],"each":[61],"investigating":[62],"a":[64],"real-world":[65],"factor":[66],"(e.g.,":[67],"noise)":[68],"impacts":[69],"inferential":[70],"accuracy.":[71]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}