{"id":"https://openalex.org/W4297102150","doi":"https://doi.org/10.1145/3539637.3556994","title":"A method for analysis of human temperament in contrast to social network data","display_name":"A method for analysis of human temperament in contrast to social network data","publication_year":2022,"publication_date":"2022-09-26","ids":{"openalex":"https://openalex.org/W4297102150","doi":"https://doi.org/10.1145/3539637.3556994"},"language":"en","primary_location":{"id":"doi:10.1145/3539637.3556994","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539637.3556994","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Brazilian Symposium on Multimedia and the Web","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/A5039219381","display_name":"Lara Mondini Martins","orcid":null},"institutions":[{"id":"https://openalex.org/I80850581","display_name":"Universidade Federal de Uberl\u00e2ndia","ror":"https://ror.org/04x3wvr31","country_code":"BR","type":"education","lineage":["https://openalex.org/I80850581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Lara Mondini Martins","raw_affiliation_strings":["Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2ndia, Brasil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2ndia, Brasil","institution_ids":["https://openalex.org/I80850581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010358381","display_name":"C\u00e1ssio De Alcantara","orcid":"https://orcid.org/0000-0002-0048-7432"},"institutions":[{"id":"https://openalex.org/I80850581","display_name":"Universidade Federal de Uberl\u00e2ndia","ror":"https://ror.org/04x3wvr31","country_code":"BR","type":"education","lineage":["https://openalex.org/I80850581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"C\u00e1ssio De Alcantara","raw_affiliation_strings":["Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2ndia, Brasil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2ndia, Brasil","institution_ids":["https://openalex.org/I80850581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009825422","display_name":"Maria Camila N. Barioni","orcid":"https://orcid.org/0000-0002-5809-0243"},"institutions":[{"id":"https://openalex.org/I80850581","display_name":"Universidade Federal de Uberl\u00e2ndia","ror":"https://ror.org/04x3wvr31","country_code":"BR","type":"education","lineage":["https://openalex.org/I80850581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Maria Camila Nardini Barioni","raw_affiliation_strings":["Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2ndia, Brasil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2ndia, Brasil","institution_ids":["https://openalex.org/I80850581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059841170","display_name":"Luiz Carlos de Oliveira J\u00fanior","orcid":"https://orcid.org/0000-0003-0852-0492"},"institutions":[{"id":"https://openalex.org/I80850581","display_name":"Universidade Federal de Uberl\u00e2ndia","ror":"https://ror.org/04x3wvr31","country_code":"BR","type":"education","lineage":["https://openalex.org/I80850581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Luiz Carlos De Oliveira J\u00fanior","raw_affiliation_strings":["Faculdade de Medicina, Universidade Federal de Uberl\u00e2ndia, Brasil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculdade de Medicina, Universidade Federal de Uberl\u00e2ndia, Brasil","institution_ids":["https://openalex.org/I80850581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042178956","display_name":"Elaine R. Faria","orcid":"https://orcid.org/0000-0001-5242-9026"},"institutions":[{"id":"https://openalex.org/I80850581","display_name":"Universidade Federal de Uberl\u00e2ndia","ror":"https://ror.org/04x3wvr31","country_code":"BR","type":"education","lineage":["https://openalex.org/I80850581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Elaine Ribeiro Faria","raw_affiliation_strings":["Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2ndia, Brasil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2ndia, Brasil","institution_ids":["https://openalex.org/I80850581"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3401,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.61858709,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"19","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13155","display_name":"Digital Communication and Language","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T13155","display_name":"Digital Communication and Language","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9973999857902527,"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/T10355","display_name":"Impact of Technology on Adolescents","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/temperament","display_name":"Temperament","score":0.8888111114501953},{"id":"https://openalex.org/keywords/feeling","display_name":"Feeling","score":0.7370141744613647},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5938491821289062},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.5028881430625916},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.48156431317329407},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4774749279022217},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.4649435579776764},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44619423151016235},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.33223044872283936},{"id":"https://openalex.org/keywords/personality","display_name":"Personality","score":0.28798288106918335},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.2801061272621155},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25210505723953247},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.23558154702186584}],"concepts":[{"id":"https://openalex.org/C61644593","wikidata":"https://www.wikidata.org/wiki/Q80157","display_name":"Temperament","level":3,"score":0.8888111114501953},{"id":"https://openalex.org/C122980154","wikidata":"https://www.wikidata.org/wiki/Q205555","display_name":"Feeling","level":2,"score":0.7370141744613647},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5938491821289062},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.5028881430625916},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.48156431317329407},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4774749279022217},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.4649435579776764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44619423151016235},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.33223044872283936},{"id":"https://openalex.org/C187288502","wikidata":"https://www.wikidata.org/wiki/Q641118","display_name":"Personality","level":2,"score":0.28798288106918335},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2801061272621155},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25210505723953247},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.23558154702186584},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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:10.1145/3539637.3556994","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539637.3556994","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Brazilian Symposium on Multimedia and the Web","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W80463681","https://openalex.org/W603795692","https://openalex.org/W2013162922","https://openalex.org/W2027103912","https://openalex.org/W2027293337","https://openalex.org/W2032308945","https://openalex.org/W2100698030","https://openalex.org/W2148563644","https://openalex.org/W2183659962","https://openalex.org/W2189339362","https://openalex.org/W2250238316","https://openalex.org/W2263228652","https://openalex.org/W2791928066","https://openalex.org/W2911317544","https://openalex.org/W2920087251","https://openalex.org/W2921081738","https://openalex.org/W2923534230","https://openalex.org/W2941434583","https://openalex.org/W2944104131","https://openalex.org/W2979787044","https://openalex.org/W3005848484","https://openalex.org/W3023633684","https://openalex.org/W3117920982","https://openalex.org/W3134742407","https://openalex.org/W4206719735","https://openalex.org/W4281856635"],"related_works":["https://openalex.org/W1583771669","https://openalex.org/W787934089","https://openalex.org/W2911603482","https://openalex.org/W3167962453","https://openalex.org/W575699006","https://openalex.org/W2136882696","https://openalex.org/W2913918867","https://openalex.org/W2238353720","https://openalex.org/W1798057852","https://openalex.org/W4205181623"],"abstract_inverted_index":{"Currently,":[0],"with":[1,108,165,179],"the":[2,5,10,51,76,86,91,120,123,143,151,160],"growth":[3],"of":[4,7,12,46,66,93,145,153,159,167],"use":[6,144,204],"social":[8,15,33,54,87,126],"networks,":[9],"possibilities":[11],"studies":[13],"on":[14],"relationships":[16,77],"and":[17,28,48,81,125,140,150,185,197,200,212],"interactions":[18],"have":[19,190],"grown":[20],"significantly.":[21],"Understanding":[22],"how":[23],"users":[24,47,166,175,189,203],"express":[25],"their":[26,30,82,138,148,156],"feelings":[27],"manifest":[29],"temperaments":[31,124],"in":[32,112,147,155,207],"networks":[34,55],"can":[35],"be":[36],"a":[37,64],"step":[38],"towards":[39],"anticipating":[40],"psychological":[41],"disorders.":[42],"Instagram":[43,208],"has":[44],"billions":[45],"is":[49,59,135],"among":[50],"most":[52],"used":[53],"today.":[56],"However,":[57],"it":[58],"still":[60],"little":[61],"explored":[62],"as":[63],"source":[65],"study":[67],"for":[68],"human":[69],"temperament.":[70],"This":[71],"work":[72],"aims":[73],"to":[74,118],"analyze":[75,119],"between":[78,122],"users\u2019":[79],"temperament":[80,162],"data":[83],"collected":[84],"from":[85],"network":[88,127],"Instagram.":[89],"For":[90],"analysis":[92],"textual":[94],"data,":[95,128],"two":[96],"sentiment":[97,103,181],"classification":[98,104],"strategies":[99],"are":[100,131,163],"proposed.":[101],"The":[102,170],"results":[105,171],"were":[106],"satisfactory,":[107],"accuracy":[109],"above":[110],"80%":[111],"three":[113],"different":[114],"databases.":[115],"In":[116],"order":[117],"relationship":[121],"statistical":[129],"tests":[130],"used.":[132],"Each":[133],"user":[134],"represented":[136],"by":[137],"positive":[139,180],"negative":[141],"captions,":[142],"emojis":[146,206],"posts,":[149],"number":[152],"likes":[154,192],"posts.":[157],"Users":[158],"same":[161],"contrasted":[164],"other":[168],"temperaments.":[169],"indicate":[172],"that":[173],"depressed":[174,211],"post":[176],"more":[177,191,205],"captions":[178,209],"than":[182,193,210],"hyperthymic,":[183,195],"angry":[184,196,213],"worried":[186,198],"users.":[187,214],"Anxious":[188],"depressed,":[194],"users,":[199],"finally,":[201],"anxious":[202]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
