{"id":"https://openalex.org/W2987294427","doi":"https://doi.org/10.1080/08839514.2019.1673037","title":"Analyzing the Brazilian Financial Market through Portuguese Sentiment Analysis in Social Media","display_name":"Analyzing the Brazilian Financial Market through Portuguese Sentiment Analysis in Social Media","publication_year":2019,"publication_date":"2019-10-31","ids":{"openalex":"https://openalex.org/W2987294427","doi":"https://doi.org/10.1080/08839514.2019.1673037","mag":"2987294427"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2019.1673037","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2019.1673037","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/20.500.12733/1657665","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110648318","display_name":"A. E. O. Carosia","orcid":null},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]},{"id":"https://openalex.org/I107371206","display_name":"Federal Institute of S\u00e3o Paulo","ror":"https://ror.org/005pn5z34","country_code":"BR","type":"education","lineage":["https://openalex.org/I107371206"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"A. E. O. Carosia","raw_affiliation_strings":["Federal Institute of S\u00e3o Paulo (IFSP), S\u00e3o Jo\u00e3o da Boa Vista, Brazil","School of Technology (FT), University of Campinas (UNICAMP), Limeira, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal Institute of S\u00e3o Paulo (IFSP), S\u00e3o Jo\u00e3o da Boa Vista, Brazil","institution_ids":["https://openalex.org/I107371206"]},{"raw_affiliation_string":"School of Technology (FT), University of Campinas (UNICAMP), Limeira, Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008918749","display_name":"Guilherme Palermo Coelho","orcid":"https://orcid.org/0000-0002-4641-0684"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"G. P. Coelho","raw_affiliation_strings":["School of Technology (FT), University of Campinas (UNICAMP), Limeira, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Technology (FT), University of Campinas (UNICAMP), Limeira, Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045617515","display_name":"Ana Estela Antunes da Silva","orcid":"https://orcid.org/0000-0001-9886-3506"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"A. E. A. Silva","raw_affiliation_strings":["School of Technology (FT), University of Campinas (UNICAMP), Limeira, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Technology (FT), University of Campinas (UNICAMP), Limeira, Brazil","institution_ids":["https://openalex.org/I181391015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5110648318"],"corresponding_institution_ids":["https://openalex.org/I107371206","https://openalex.org/I181391015"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":6.9966,"has_fulltext":false,"cited_by_count":75,"citation_normalized_percentile":{"value":0.97040798,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"34","issue":"1","first_page":"1","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9896000027656555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7949913740158081},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.6976662278175354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6973162889480591},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.6796203255653381},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5603069067001343},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5309605002403259},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49717405438423157},{"id":"https://openalex.org/keywords/portuguese","display_name":"Portuguese","score":0.488424688577652},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.48514804244041443},{"id":"https://openalex.org/keywords/financial-market","display_name":"Financial market","score":0.4358670711517334},{"id":"https://openalex.org/keywords/stock-market-prediction","display_name":"Stock market prediction","score":0.43253010511398315},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.41286996006965637},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4075820744037628},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.18848466873168945},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.1863614320755005},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.18029823899269104},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14950650930404663}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7949913740158081},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.6976662278175354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6973162889480591},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.6796203255653381},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5603069067001343},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5309605002403259},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49717405438423157},{"id":"https://openalex.org/C35219183","wikidata":"https://www.wikidata.org/wiki/Q5146","display_name":"Portuguese","level":2,"score":0.488424688577652},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.48514804244041443},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.4358670711517334},{"id":"https://openalex.org/C2776256503","wikidata":"https://www.wikidata.org/wiki/Q7617906","display_name":"Stock market prediction","level":4,"score":0.43253010511398315},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.41286996006965637},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4075820744037628},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.18848466873168945},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.1863614320755005},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.18029823899269104},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14950650930404663},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/08839514.2019.1673037","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2019.1673037","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6fd2c4245bce4777915f773578d64ec1","is_oa":false,"landing_page_url":"https://doaj.org/article/6fd2c4245bce4777915f773578d64ec1","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 34, Iss 1, Pp 1-19 (2020)","raw_type":"article"},{"id":"pmh:oai:https://www.repositorio.unicamp.br/:1201594","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.12733/1657665","pdf_url":null,"source":{"id":"https://openalex.org/S4306402641","display_name":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Cient\u00edficas)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4383465926","host_organization_name":"LA Referencia","host_organization_lineage":["https://openalex.org/I4383465926"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"reponame:Reposit\u00f3rio da Produ\u00e7\u00e3o Cient\u00edfica e Intelectual da Unicamp","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:https://www.repositorio.unicamp.br/:1201594","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.12733/1657665","pdf_url":null,"source":{"id":"https://openalex.org/S4306402641","display_name":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Cient\u00edficas)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4383465926","host_organization_name":"LA Referencia","host_organization_lineage":["https://openalex.org/I4383465926"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"reponame:Reposit\u00f3rio da Produ\u00e7\u00e3o Cient\u00edfica e Intelectual da Unicamp","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W19790595","https://openalex.org/W1762172548","https://openalex.org/W1984430235","https://openalex.org/W2002011878","https://openalex.org/W2004463884","https://openalex.org/W2039796390","https://openalex.org/W2050643653","https://openalex.org/W2059126127","https://openalex.org/W2131773668","https://openalex.org/W2138293190","https://openalex.org/W2171468534","https://openalex.org/W2215376118","https://openalex.org/W2243366343","https://openalex.org/W2293665115","https://openalex.org/W2401379394","https://openalex.org/W2515298219","https://openalex.org/W2548006041","https://openalex.org/W2746308373","https://openalex.org/W2762466482","https://openalex.org/W2790343801","https://openalex.org/W2885108704","https://openalex.org/W3121285418","https://openalex.org/W3125952890","https://openalex.org/W4205184193","https://openalex.org/W4249701336"],"related_works":["https://openalex.org/W3089396779","https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2596247554","https://openalex.org/W4301373556","https://openalex.org/W3021501837","https://openalex.org/W2799178524","https://openalex.org/W1969396493","https://openalex.org/W2993224164"],"abstract_inverted_index":{"According":[0],"to":[1,35,53,66,105,152,184,211,228],"the":[2,22,68,77,81,86,98,110,145,181,186,191,208,221,229],"Efficient":[3],"Market":[4],"Hypothesis,":[5],"financial":[6,78],"market":[7,23,113,194,231],"movements":[8],"are":[9,240],"dependent":[10],"on":[11,21,76,91,97],"news":[12,71],"and":[13,42,57,72,94,134,175,178,190],"external":[14],"events":[15],"that":[16,204,220],"have":[17],"a":[18,28,107,160],"significant":[19],"impact":[20,69],"value":[24],"of":[25,31,70,88,109,125,149],"companies.":[26],"Thus,":[27],"great":[29],"amount":[30],"applications":[32],"has":[33],"arisen":[34],"explore":[36],"this":[37,155],"knowledge":[38],"through":[39,115],"automatic":[40],"sentiment":[41,89,223],"opinion":[43],"extraction.":[44],"The":[45,141],"technique":[46,210],"known":[47],"as":[48,235,237],"Sentiment":[49],"Analysis":[50],"(SA)":[51],"aims":[52,104],"analyze":[54],"opinions,":[55],"sentiments,":[56],"emotions":[58],"present":[59],"in":[60,117,214,224],"unstructured":[61],"data,":[62],"leading":[63],"many":[64],"papers":[65],"address":[67],"social":[73,92,225],"media":[74,93,226],"publications":[75],"market.":[79,101],"However,":[80],"literature":[82],"lacks":[83],"works":[84],"considering":[85,119,196],"effects":[87],"available":[90],"its":[95],"impacts":[96],"Brazilian":[99,111,146,192],"stock":[100,112,193,230],"This":[102],"work":[103],"conduct":[106],"study":[108,162],"movement":[114,195],"SA":[116,164,213],"Twitter":[118],"tree":[120],"perspectives:":[121],"(i)":[122],"absolute":[123],"number":[124],"tweet":[126],"sentiments;":[127],"(ii)":[128],"tweets":[129,136],"sentiments":[130,137,189],"weighted":[131,138],"by":[132,139],"favorites;":[133],"(iii)":[135],"retweets.":[140],"analyzed":[142],"period":[143,148],"was":[144,207],"electoral":[147],"2018":[150],"(01-Oct-2018":[151],"31-Dec-2018).":[153],"In":[154,216],"paper,":[156],"we":[157,218],"first":[158],"developed":[159],"comparison":[161],"with":[163],"Machine":[165],"Learning":[166],"techniques":[167],"(Naive":[168],"Bayes,":[169],"Support":[170],"Vector":[171],"Machines,":[172],"Maximum":[173],"Entropy,":[174],"Multilayer":[176,205],"Perceptron)":[177],"then":[179],"applied":[180],"best":[182,209],"algorithm":[183],"establish":[185],"relations":[187],"between":[188],"different":[197],"time":[198],"frames":[199],"(windows":[200],"sizes).":[201],"Results":[202],"indicate":[203],"Perceptron":[206],"perform":[212],"Portuguese.":[215],"addition,":[217],"observed":[219],"predominant":[222],"relates":[227],"movement,":[232],"improving":[233],"accuracy":[234],"long":[236],"windows":[238],"sizes":[239],"increased.":[241]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}