{"id":"https://openalex.org/W2405287689","doi":"https://doi.org/10.1109/taffc.2016.2571284","title":"Applications of Automated Facial Coding in Media Measurement","display_name":"Applications of Automated Facial Coding in Media Measurement","publication_year":2016,"publication_date":"2016-05-22","ids":{"openalex":"https://openalex.org/W2405287689","doi":"https://doi.org/10.1109/taffc.2016.2571284","mag":"2405287689"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2016.2571284","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2016.2571284","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-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/A5100681741","display_name":"Daniel McDuff","orcid":"https://orcid.org/0000-0001-7313-0082"},"institutions":[{"id":"https://openalex.org/I4210127225","display_name":"Affectiva (United States)","ror":"https://ror.org/0322cev20","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127225"]},{"id":"https://openalex.org/I4210142372","display_name":"Human Media","ror":"https://ror.org/04072nk43","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210142372"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel McDuff","raw_affiliation_strings":["Affectiva, Waltham, MA","MIT Media Lab, Cambridge, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Affectiva, Waltham, MA","institution_ids":["https://openalex.org/I4210127225"]},{"raw_affiliation_string":"MIT Media Lab, Cambridge, MA","institution_ids":["https://openalex.org/I4210142372"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051143813","display_name":"Rana el Kaliouby","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127225","display_name":"Affectiva (United States)","ror":"https://ror.org/0322cev20","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rana el Kaliouby","raw_affiliation_strings":["Affectiva, Waltham, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Affectiva, Waltham, MA","institution_ids":["https://openalex.org/I4210127225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1601,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.84688315,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"8","issue":"2","first_page":"148","last_page":"160"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11448","display_name":"Face recognition and analysis","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10667","display_name":"Emotion and Mood Recognition","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11094","display_name":"Face Recognition and Perception","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7423221468925476},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.6164973378181458},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.5073663592338562},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4492546021938324},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.42704036831855774},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.38190168142318726},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3711090683937073},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3344610035419464}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7423221468925476},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.6164973378181458},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.5073663592338562},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4492546021938324},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.42704036831855774},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.38190168142318726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3711090683937073},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3344610035419464},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taffc.2016.2571284","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2016.2571284","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4000000059604645,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320273","display_name":"University of Cambridge","ror":"https://ror.org/013meh722"},{"id":"https://openalex.org/F4320321148","display_name":"Cairo University","ror":"https://ror.org/03q21mh05"},{"id":"https://openalex.org/F4320325655","display_name":"American University in Cairo","ror":"https://ror.org/0176yqn58"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W84543019","https://openalex.org/W88081813","https://openalex.org/W164929510","https://openalex.org/W276347511","https://openalex.org/W647196612","https://openalex.org/W1527013143","https://openalex.org/W1528664920","https://openalex.org/W1537320369","https://openalex.org/W1547435830","https://openalex.org/W1559582325","https://openalex.org/W1596947417","https://openalex.org/W1708911126","https://openalex.org/W1813125012","https://openalex.org/W1971825121","https://openalex.org/W1978383016","https://openalex.org/W1982709543","https://openalex.org/W1986046374","https://openalex.org/W1989426692","https://openalex.org/W1991457441","https://openalex.org/W1994616049","https://openalex.org/W2001453824","https://openalex.org/W2003249666","https://openalex.org/W2003649326","https://openalex.org/W2008821584","https://openalex.org/W2024221294","https://openalex.org/W2028251274","https://openalex.org/W2028899742","https://openalex.org/W2035046981","https://openalex.org/W2036593095","https://openalex.org/W2036751297","https://openalex.org/W2042819969","https://openalex.org/W2045826950","https://openalex.org/W2055531799","https://openalex.org/W2062733121","https://openalex.org/W2095809036","https://openalex.org/W2097397553","https://openalex.org/W2098935012","https://openalex.org/W2100127573","https://openalex.org/W2104535712","https://openalex.org/W2105410877","https://openalex.org/W2106508100","https://openalex.org/W2118850497","https://openalex.org/W2120146197","https://openalex.org/W2120856140","https://openalex.org/W2132006104","https://openalex.org/W2135978202","https://openalex.org/W2147449317","https://openalex.org/W2151539117","https://openalex.org/W2152887989","https://openalex.org/W2157285372","https://openalex.org/W2161969291","https://openalex.org/W2163301185","https://openalex.org/W2163352848","https://openalex.org/W2164186291","https://openalex.org/W2164598857","https://openalex.org/W2164699598","https://openalex.org/W2166827712","https://openalex.org/W2168893862","https://openalex.org/W2184045248","https://openalex.org/W2299275441","https://openalex.org/W2316503402","https://openalex.org/W2551442547","https://openalex.org/W2616332126","https://openalex.org/W2946287218","https://openalex.org/W2988376401","https://openalex.org/W4231875141","https://openalex.org/W4285719527","https://openalex.org/W6635653641","https://openalex.org/W6770527548"],"related_works":["https://openalex.org/W2123478443","https://openalex.org/W2115635058","https://openalex.org/W2081765545","https://openalex.org/W2088830394","https://openalex.org/W2088050694","https://openalex.org/W4319336808","https://openalex.org/W2153939644","https://openalex.org/W4386320679","https://openalex.org/W2012415311","https://openalex.org/W1522488816"],"abstract_inverted_index":{"Facial":[0,26],"coding":[1,95],"has":[2],"become":[3],"a":[4,127,188],"common":[5],"tool":[6],"in":[7,43,78,116,126],"media":[8,161,177],"measurement,":[9],"with":[10],"large":[11],"companies":[12],"(e.g.,":[13],"Unilever)":[14],"using":[15],"it":[16],"to":[17,58,122,159,168,192],"test":[18],"all":[19],"of":[20,32,92,97,134,173],"their":[21],"new":[22],"video":[23,71,98],"ad":[24],"content.":[25,162],"reactions":[27],"capture":[28],"the":[29,82,87,120,132,146],"in-the-moment":[30],"response":[31],"an":[33],"individual":[34],"and":[35,62,104,129,142,153,183],"these":[36,111,135,181],"data":[37,72,112,136,182],"complement":[38],"self-report":[39],"measures.":[40,144],"Two":[41],"advancements":[42],"affective":[44],"computing":[45],"have":[46,151],"made":[47],"measurement":[48],"possible":[49],"at":[50],"scale:":[51],"1)":[52],"computer":[53],"vision":[54],"algorithms":[55],"are":[56,73],"used":[57,115],"automatically":[59],"code":[60],"sign":[61],"message":[63],"judgments":[64],"based":[65],"on":[66],"facial":[67,94,124,194],"muscle":[68],"movements,":[69],"2)":[70],"collected":[74,152],"by":[75],"recording":[76],"responses":[77,158,174,195],"everyday":[79,160],"environments":[80],"via":[81],"viewer's":[83],"own":[84],"webcam":[85],"over":[86,155],"Internet.":[88],"We":[89,108,179],"present":[90,180],"results":[91],"online":[93],"studies":[96],"ads,":[99],"movie":[100],"trailers,":[101],"political":[102],"content,":[103],"long-form":[105],"TV":[106],"shows.":[107],"explain":[109],"how":[110],"can":[113],"be":[114],"market":[117],"research.":[118],"Despite":[119],"ability":[121],"measure":[123],"behavior":[125],"scalable":[128],"quantifiable":[130],"way,":[131],"interpretation":[133],"is":[137],"still":[138],"challenging":[139],"without":[140],"baselines":[141],"comparative":[143],"Over":[145],"past":[147],"four":[148],"years":[149],"we":[150],"coded":[154],"two":[156],"million":[157],"Our":[163],"huge":[164],"dataset":[165],"allows":[166],"us":[167],"calculate":[169],"reliable":[170],"normative":[171],"distributions":[172],"across":[175],"different":[176],"types.":[178],"argue":[184],"that":[185],"this":[186],"provides":[187],"context":[189],"within":[190],"which":[191],"interpret":[193],"more":[196],"accurately.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
